ai - data scientist · a data scientist needs to have excellent analytical skills, attention to...

Qualification Pack

AI - Data Scientist

Electives: Model Risk Assessment/ Model Business Performance/ Visualizations

QP Code: SSC/Q8104

NSQF Level: 7

IT-ITeS Sector Skill Council || IT-ITeS Sector Skill Council, NASSCOM,Plot No - 7, 8, 9 & 10,3rd Floor,

Sector 126, Noida Uttar Pradesh - 201303

IT-ITeS Sector Skill Council 1

Qualification Pack

Contents

SSC/Q8104: AI - Data Scientist ............................................................................................................... 3

Brief Job Description ........................................................................................................................ 3 Applicable National Occupational Standards (NOS) ................................................................................ 3

Compulsory NOS ............................................................................................................................. 3 Elective 1: Model Risk Assessment .................................................................................................. 3 Elective 2: Model Business Performance ......................................................................................... 3 Elective 3: Visualizations .................................................................................................................. 4 Qualification Pack (QP) Parameters ................................................................................................. 4

SSC/N8101: Import Data as per specifications ........................................................................................ 5 SSC/N8102: Pre process data as per specifications ................................................................................ 9 SSC/N8103: Perform exploratory data analysis as per specifications .................................................... 13 SSC/N8105: Apply pre-designed algorithmic models to specified use cases ......................................... 17 SSC/N8104: Perform research and design of algorithmic models ......................................................... 21 SSC/N9001: Manage your work to meet requirements .......................................................................... 27 SSC/N9002: Work effectively with colleagues ....................................................................................... 31 SSC/N9004: Provide data/information in standard formats .................................................................... 35 SSC/N9006: Build and Maintain relationships in a Workplace ............................................................... 39 SSC/N9007: Build and Maintain client satisfaction ................................................................................ 43 SSC/N9010: Convince others to take appropriate action in different situations ...................................... 47 SSC/N9014: Maintain an inclusive, environmentally sustainable workplace……………………………... 50 SSC/N8106: Evaluate risk of deploying algorithmic models ................................................................... 54 SSC/N8107: Evaluate business performance of algorithmic models ..................................................... 58 SSC/N8108: Define business outcomes and create visualizations from results of the analysis ............. 62 Assessment Guidelines and Weightage ................................................................................................ 66

Assessment Guidelines .................................................................................................................. 66 Assessment Weightage .................................................................................................................. 66


Qualification Pack

SSC/Q8104: AI - Data Scientist

Brief Job Description

Individuals at this job are responsible for performing different elements of data science such as importing

and pre processing data, performing exploratory analysis, research and design of algorithmic models.

Personal Attributes

A data scientist needs to have excellent analytical skills, attention to detail, critical thinking and problem

solving ability. S/he needs to have strong communication skills and a superior understanding of the

business to work with stakeholders and decision makers across the organization.

Applicable National Occupational Standards (NOS)

Compulsory NOS:

1. SSC/N8101: Import Data as per specifications

2. SSC/N8102: Preprocess data as per specifications

3. SSC/N8103: Perform exploratory data analysis as per specifications

4. SSC/N8105: Apply pre-designed algorithmic models to specified use cases

5. SSC/N8104: Perform research and design of algorithmic models

6. SSC/N9001: Manage your work to meet requirements

7. SSC/N9002: Work effectively with colleagues

8. SSC/N9004: Provide data/information in standard formats

9. SSC/N9006: Build and Maintain relationships in a Workplace

10. SSC/N9007: Build and Maintain client satisfaction

11. SSC/N9010: Convince others to take appropriate action in different situations

12. SSC/N9014: Maintain an inclusive, environmentally sustainable workplace Electives (mandatory to select at least one):

Elective 1: Model Risk Assessment

The individual would evaluate risks to model and develop mitigation measures

1. SSC/N8106: Evaluate risk of deploying algorithmic models


Qualification Pack

Elective 2: Model Business Performance

The individual would evaluate performance of the model at meeting business outcomes

1. SSC/N8107: Evaluate business performance of algorithmic models

Elective 3: Visualizations

The individual would define business outcomes based on the results of the analysis and create

visualizations to present said outcomes to relevant stakeholders

1. SSC/N8108: Define business outcomes and create visualizations from results of the analysis

Qualification Pack (QP) Parameters

Sector IT-ITeS

Sub-Sector Future Skills

Primary Occupation Artificial Intelligence and Big Data Analytics

Secondary Occupation

Country India

NSQF Level 7

Aligned to NCO/ISCO/ISIC NCO-2015/NIL

Code

Minimum Educational Graduate

Qualification & (Engineering/Technology/Statistics/Mathematics/Computer

Experience Science) with 5-10 Years of experience Recommended

Minimum Level of

12th Class Education for Training in

School

Pre-Requisite License or NA

Training

Minimum Job Entry Age 21 Years

Last Reviewed On 31/03/2020

Next Review Date 31/03/2025

NSQC Approval Date NA

Version 2.0


Qualification Pack

SSC/N8101: Import Data as per specifications

Description

This unit is about using a variety of techniques to import data into datasets or data frames.

Scope

This unit/task covers the following:

• Define data type and sources

• Acquire the data

Elements and Performance Criteria

Define data type and sources To be competent, the user/individual on the job must be able to:

PC1. identify the objective of the analysis PC2. define the type of data to be imported PC3. define the volume of data to be imported PC4. define the key variables to be imported PC5. identify suitable sources for the data Acquire the data To be competent, the user/individual on the job must be able to:

PC6. perform operations to acquire the data and store it in datasets or data frames

PC7. populate metadata for the imported data PC8. validate imported data using appropriate tools & processes PC9. validate the desired output with the relevant stakeholders within the organization, if required

Knowledge and Understanding (KU)

The individual on the job needs to know and understand:

KU1. the purpose and aims of the statistical analysis being undertaken

KU2. organizational policies, procedures and guidelines which relate to importing and sharing data KU3. different data sources and how to access documents and information from data sources KU4. who to consult when importing data KU5. the range of standard templates and tools available and how to use them KU6. the difference between various types of data. For example, enterprise vs consumer data

qualitative vs quantitative data processed vs unprocessed data KU7. statistical analysis Softwares, packages, libraries and tools that can be used to import &

validate data such as R or Pandas KU8. functions to read data from various file formats and import it to a dataset or data frame KU9. the metadata associated with imported data and how to populate it


Qualification Pack

KU10. how to store and retrieve information

KU11. various operating systems such as linux, ubuntu, or windows

Generic Skills (GS)

User/individual on the job needs to know how to:

GS1. follow instructions, guidelines, procedures, rules and service level agreements

GS2. evaluate impact analysis of the various actions performed and disseminate relevant

information to others GS3. check the work completion without errors


Qualification Pack

Assessment Criteria

Assessment Criteria for Outcomes Theory Practical Project Viva

Marks Marks Marks Marks

Define data type and sources 20 35 - -

PC1. identify the objective of the analysis 5 5 - -

PC2. define the type of data to be imported 2 5 - -

PC3. define the volume of data to be 3 5 - -

imported

PC4. define the key variables to be 5 10 - -

imported

PC5. identify suitable sources for the data 5 10 - -

Acquire the data 10 35 - -

PC6. perform operations to acquire the data 5 15 - -

and store it in datasets or data frames

PC7. populate metadata for the imported 5 10 - -

data

PC8. validate imported data using - 5 - -

appropriate tools & processes

PC9. validate the desired output with the

- 5 - - relevant stakeholders within the

organization, if required

NOS Total 30 70 - -


Qualification Pack

National Occupational Standards (NOS) Parameters

NOS Code SSC/N8101

NOS Name Import Data as per specifications

Sector IT-ITeS


Primary Occupation Artificial Intelligence & Big Data Analytics


NSQF Level 6

Credits TBD

Version 2.0

Last Reviewed Date 31/03/2020


NSQC Clearance Date NA


Qualification Pack

SSC/N8102: Pre-process data as per specifications

Description

This unit is about using a variety of techniques to pre-process data i.e. clean and transform the data.

Scope


• Define the dataset

• Perform data pre-processing operations


Define the dataset To be competent, the user/individual on the job must be able to:

PC1. define the format and structure for the dataset PC2. define indexes and organize variables as per the defined format PC3. identify data types for each variable of the dataset Perform data pre-processing operations To be competent, the user/individual on the job must be able to:

PC4. identify and fix missing values in each variable of the dataset PC5. identify and fix incorrect data types in each variable of the dataset PC6. sort the data and create subsets of the data as required PC7. perform operations to transform data types of variables as required PC8. identify and deal with data redundancy by normalizing the dataset PC9. validate preprocessed data using appropriate tools and processes




KU2. organizational policies, procedures and guidelines which relate to pre-processing and sharing data

KU3. data sources and how to access documents and information from data sources KU4. whom to consult while pre-processing data KU5. the range of standard templates and tools available and how to use them KU6. the difference between various types of data. For example, qualitative vs quantitative data

processed vs unprocessed data discrete vs continuous data KU7. statistical analysis software, packages, libraries and tools that can be used to pre-

process data such as R or Pandas KU8. functions to identify and remove missing values


Qualification Pack

KU9. functions to identify and transform data types of variables such as integer, float, character KU10. methodological approaches for normalizing the dataset such as standard score, feature

scaling, etc. KU11. data formats and structures KU12. identification of anomalies in data KU13. various databases and operating systems

Generic Skills (GS)



information to others GS2. analyze data and understand its implications on business

GS3. check the work completion without errors


Qualification Pack

Assessment Criteria



Define the dataset 5 15 - -

PC1. define the format and structure for the - 5 - -

dataset

PC2. define indexes and organize variables 2 3 - -

as per the defined format

PC3. identify data types for each variable of 3 7 - -

the dataset

Perform data pre-processing operations 25 55 - -

PC4. identify and fix missing values in each 5 10 - -

variable of the dataset

PC5. identify and fix incorrect data types in 5 10 - -

each variable of the dataset

PC6. sort the data and create subsets of the 5 10 - -

data as required

PC7. perform operations to transform data 5 10 - -

types of variables as required

PC8. identify and deal with data redundancy 5 10 - -

by normalizing the dataset

PC9. validate pre-processed data using - 5 - -

appropriate tools and processes

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8102

NOS Name Preprocess data as per specifications

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

SSC/N8103: Perform exploratory data analysis as per specifications

Description

This unit is about using a variety of techniques to perform exploratory analysis to describe and summarize

data for internal and external clients

Scope


• Define the dataset

• Summarize and optimize the dataset


Define the dataset To be competent, the user/individual on the job must be able to:

PC1. identify the data types for each variable of the dataset

PC2. identify the key variables required for modelling or analysis

Summarize and optimize the dataset To be competent, the user/individual on the job must be able to:

PC3. use statistical techniques to summarize the key variables in the dataset

PC4. describe summary statistics for key variables using graphical formats PC5. perform dimension reduction to optimize the variables in the dataset, if required

PC6. define the correlation factors using clustering and other techniques PC7. validate data using appropriate tools and processes

PC8. repeat the analysis iteratively to arrive at optimal results PC9. validate the final output in consultation with the relevant stakeholders

PC10. gain inferences from the final output of the data analysis PC11. develop a hypothesis model to explain the discovered inferences PC12. evaluate the results of the analysis and define business outcomes PC13. define prescriptive actions based on the defined business outcomes




KU2. organizational policies, procedures and guidelines which relate to performing explanatory

analysis KU3. data sources and how to access documents and information from data sources KU4. organizational policies and procedures for sharing data KU5. whom to consult when performing explanatory analysis


Qualification Pack

KU6. the range of standard templates and tools available and how to use them

KU7. the difference between various types of data. For example, qualitative vs quantitative data

processed vs unprocessed data discrete vs continuous data KU8. statistical analysis software, packages, libraries and tools that can be used to pre-process

and summarize data such as R, NumPy, Statistical models, or Pandas

KU9. functions to summarize variables across different data types such as integer, float, or

character KU10. graphical formats to describe summary statistics KU11. methodological approaches for dimension reduction such as PCA, LDA, or NMF KU12. methodological approaches for defining correlations between variables such as the scatter

diagram method, correlation coefficients, method of least squares KU13. multivariate visualizations, for mapping and understanding interactions between different

fields in the data KU14. The inferences from analysed data and explain it using a hypothesis model KU15. types of prescriptive actions KU16. identification of anomalies in data KU17. various operating systems such as linux, ubuntu, or windows

Generic Skills (GS)



information to others GS2. analyze data and understand its implications on business


Qualification Pack

Assessment Criteria



Define the dataset 5 8 - -

PC1. identify the data types for each variable 2 3 - -

of the dataset

PC2. identify the key variables required for 3 5 - -

modelling or analysis

Summarize and optimize the dataset 25 62 - -

PC3. use statistical techniques to summarize 5 10 - -

the key variables in the dataset

PC4. describe summary statistics for key 2 6 - -

variables using graphical formats

PC5. perform dimension reduction to optimize 3 5 - -

the variables in the dataset, if required

PC6. define the correlation factors using 3 5 - -

clustering and other techniques

PC7. validate data using appropriate tools and - 5 - -

processes

PC8. repeat the analysis iteratively to arrive at 2 6 - -

optimal results

PC9. validate the final output in consultation - 5 - -

with the relevant stakeholders

PC10. gain inferences from the final output of 2 5 - -

the data analysis

PC11. develop a hypothesis model to explain 2 5 - -

the discovered inferences

PC12. evaluate the results of the analysis and 3 5 - -

define business outcomes

PC13. define prescriptive actions based on the 3 5 - -

defined business outcomes

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8103

NOS Name Perform exploratory data analysis as per specifications

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

SSC/N8105: Apply pre-designed algorithmic models to specified use cases

Description

This unit is about applying a variety of pre-designed algorithmic models to specified use cases for internal

and external clients.

Scope


Define hypothesis

Apply and optimize model


Define hypothesis To be competent, the user/individual on the job must be able to:

PC1. identify the objective of the analysis PC2. evaluate the dataset to determine a suitable approach PC3. identify suitable libraries, packages, frameworks, applications to address the objective Apply and Optimize Model To be competent, the user/individual on the job must be able to:

PC4. select suitable algorithmic models from available statistical analysis softwares, packages,

libraries or tools PC5. apply the model for various use cases and scenarios such as vision, text recognition, image

recognition, natural language processing etc. PC6. optimize selected algorithmic models to resolve any shortcomings or defects PC7. iterate the model in consultation with relevant stakeholders till the desired performance or

quality of output is achieved PC8. validate the models implemented using appropriate tools and processes PC9. create documentation on applied algorithmic models for future references and versioning




KU2. organizational policies, procedures and guidelines which relate to applying and

documenting algorithmic models KU3. different data sources and how to access documents and information from data sources

KU4. organizational policies and procedures for sharing data KU5. whom to consult when applying algorithmic models


Qualification Pack

KU6. the range of standard templates and tools available and how to use Them

KU7. statistical analysis software, packages, libraries or tools with pre-designed algorithmic

models such as Mahout, BigML, Data Robot, Knime, Tensorflow KU8. programming languages that can be used to design algorithmic models such as python,

ruby, C, java, c++, c# etc. KU9. different use cases and the suitability of various algorithmic models to address them

KU10. how to build and test a hypothesis KU11. cloud or distributed computing platforms such as AWS, Azure, Hadoop, their affiliated

services and how to use these KU12. how to identify and refer anomalies in data KU13. various operating systems such as linux, ubuntu, or Windows

Generic Skills (GS)



information to others GS2. analyze data, models and understand its implications on business performance

GS3. check work completion without errors


Qualification Pack

Assessment Criteria



Define hypothesis 8 17 - -


PC2. evaluate the dataset to determine a 3 7 - -

suitable approach

PC3. identify suitable libraries, packages,

3 7 - - frameworks, applications to address the

objective

Apply and Optimize Model 22 53 - -

PC4. select suitable algorithmic models from

5 15 - - available statistical analysis softwares,

packages, libraries or tools

PC5. apply the model for various use cases and scenarios such as vision, text recognition,

10 15 - - image recognition, natural language processing

etc.

PC6. optimize selected algorithmic models to 5 10 - -

resolve any shortcomings or defects

PC7. iterate the model in consultation with

2 3 - - relevant stakeholders till the desired

performance or quality of output is achieved

PC8. validate the models implemented using - 5 - -


PC9. create documentation on applied

- 5 - - algorithmic models for future references and

versioning

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8105

NOS Name Apply pre-designed algorithmic models to specified use cases

Sector IT-ITeS




NSQF Level 7

Credits TBD

Version 2.0





Qualification Pack

SSC/N8104: Perform research and design of algorithmic models

Description

This unit is about performing research and designing a variety of algorithmic models for internal and

external clients.

Scope

The scope covers the following:

Define hypothesis Select model Prototype and design


Define hypothesis To be competent, the user/individual on the job must be able to:

PC1. identify the objective of the analysis PC2. develop a hypothesis based on the objective of the analysis PC3. identify suitable libraries, packages, frameworks, applications to address the objective Select model To be competent, the user/individual on the job must be able to:

PC4. identify mode of learning, i.e. supervised or unsupervised PC5. conduct research on existing statistical models to evaluate fitment with the objective PC6. depending on the use case, identify if neural networks or deep learning models can be built PC7. optimize the existing statistical models as per need PC8. identify suitable statistical models on the basis of data volumes and key variables

PC9. define connectors or combinations of key variables for each statistical model Prototype and Design To be competent, the user/individual on the job must be able to:

PC10. determine and collect the training data PC11. design and prototype algorithmic model

PC12. identify and resolve overfitting or underfitting of algorithmic model

PC13. identify and resolve residual and dispersion errors with data PC14. define data flows such as human-in-the-loop constraints required to reinforce algorithmic

models PC15. define and quantify success metrics for the algorithmic model PC16. create documentation on designed algorithmic models for future references and versioning PC17. retrain datasets that have been used for supervised learning on a continuous basis PC18. validate designed models using appropriate tools and processes


Qualification Pack

PC19. Iterate the process to fine-tune the model till the desired quality of output or performance is

achieved



KU1. the purpose and aims of the analysis being undertaken

KU2. organizational policies, procedures and guidelines which relate to designing and

documenting algorithmic models KU3. different data sources and how to access documents and information from data sources

KU4. organizational policies and procedures for sharing data KU5. whom to involve when designing algorithmic models KU6. the range of standard templates and tools available and how to use them KU7. ability to develop experimental and analytical plans for data modelling, use of strong

baselines, ability to accurately determine cause and effect relations KU8. probability theory concepts such as probability distributions, statistical significance, hypothesis

testing and regression KU9. Bayesian thinking concepts such as conditional probability, priors and posteriors, and

maximum likelihood KU11. strong research experience in deep learning, reinforcement learning and other machine

learning algorithms and their usage KU12. programming languages that can be used to design algorithmic models such as python,

ruby, C, java, c++ or c# KU13. use cases and the suitability of various algorithmic models to address them

KU14. how to build and test a hypothesis KU15. supervised or unsupervised learning KU16. Evaluation of data volumes and key variables KU17. how to define combinations of key variables KU18. optimization of overfitting or underfitting of algorithmic models and residual and dispersion

errors KU19. how to define data flows such as human-in-the-loop constraints required to reinforce

algorithmic models KU20. cloud or distributed computing platforms such as AWS, Azure, Hadoop, their affiliated

services and how to use these KU21. Identification of anomalies in data KU22. various operating systems such as linux, ubuntu, or Windows

Generic Skills (GS)



information to others


Qualification Pack

GS2. analyze data, models and understand its implications on business performance

GS3. check work completion without errors


Qualification Pack

Assessment Criteria



Define hypothesis 2 7 - -

PC1. identify the objective of the analysis - 2 - -

PC2. develop a hypothesis based on the 1 2 - -

objective of the analysis

PC3. identify suitable libraries, packages,

1 3 - - frameworks, applications to address the

objective

Select model 12 24 - -

PC4. identify mode of learning, i.e. supervised or 2 4 - -

unsupervised

PC5. conduct research on existing statistical 2 4 - -

models to evaluate fitment with the objective

PC6. depending on the use case, identify if

2 4 - - neural networks or deep learning models can be

built

PC7. optimize the existing statistical models as 2 4 - -

per need

PC8. identify suitable statistical models on the 2 4 - -

basis of data volumes and key variables

PC9. define connectors or combinations of key 2 4 - -

variables for each statistical model

Prototype and Design 14 41 - -

PC10. determine and collect the training data 2 4 - -

PC11. design and prototype algorithmic model 3 6 - -

PC12. identify and resolve overfitting or 2 4 - -

underfitting of algorithmic model

PC13. identify and resolve residual and 2 4 - -

dispersion errors with data

PC14. define data flows such as human-in-the-

1 3 - - loop constraints required to reinforce algorithmic

models


Qualification Pack



PC15. define and quantify success metrics for 2 4 - -

the algorithmic model

PC16. create documentation on designed

- 4 - - algorithmic models for future references and

versioning

PC17. retrain datasets that have been used for 2 4 - -

supervised learning on a continuous basis

PC18. validate designed models using - 4 - -


PC19. Iterate the process to fine-tune the model

- 4 - - till the desired quality of output or performance

is achieved

NOS Total 28 72 - -


Qualification Pack


NOS Code SSC/N8104

NOS Name Perform research and design of algorithmic models

Sector IT-ITeS



Secondary Occupation Artificial Intelligence and Big Data Analytics

NSQF Level 7

Credits TBD

Version 2.0





Qualification Pack

SSC/N9001: Manage your work to meet requirements

Description

This unit is about planning and organizing your work in order to complete it to the required standards on

time.

Scope


• Utilize resources

• Ensure compliance


To be competent, the user/individual on the job must be able to: Utilize resources

PC1. establish and agree work requirements with appropriate people PC2. keep immediate work area clean and tidy PC3. utilize time effectively PC4. use resources correctly and efficiently PC5. treat confidential information correctly Ensure compliance PC6. work in line with organizations policies and procedures PC7. work within the limits of job role PC8. obtain guidance from appropriate people, where necessary

PC9. ensure work meets the agreed requirements



KU1. priorities for the area of work

KU2. role, responsibilities, limits of the responsibilities and whom these must be agreed with, as

well as when to involve others

KU3. the importance of having a tidy work area and how to do this

KU4. how to prioritize the workload according to urgency and importance and the benefits of this

KU5. the organizations policies and procedures, especially for dealing with confidential information,

and the importance of complying with these

KU6. the purpose of keeping others updated with the progress of work

KU7. the purpose and value of being flexible and adapting work plans to reflect change

KU8. the importance of completing work accurately and how to do this IT-ITeS Sector Skill Council 27

Qualification Pack

KU9. appropriate timescales for completing the work and the implications of not meeting these for

self and the organization KU10. The resources needed for the work and how to obtain and use these

Generic Skills (GS)


GS1. read instructions, guidelines, procedures, rules and service level agreements GS2. ask for clarification and advice from line managers GS3. communicate orally with colleagues GS4. make decisions on suitable courses

GS5. plan and organize the work to achieve targets and deadlines

GS6. agree objectives and work requirements GS7. deliver consistent and reliable service to customers GS8. check that the work meets customer requirements GS9. refer anomalies to the line manager GS10. seek clarification on problems from others GS11. provide relevant information to others GS12. analyze needs, requirements and dependencies in order to meet the work requirements

GS13. apply judgment to different situations GS14. ensure the work is complete and free from errors GS15. get the work checked by peers GS16. work effectively in a team environment GS17. use information technology effectively, to input and/or extract data accurately GS18. identify and refer anomalies in data GS19. store and retrieve information GS20. keep up to date with changes, procedures and practices in the role IT-ITeS Sector Skill Council 28

Qualification Pack

Assessment Criteria



25 75 - -

PC1. establish and agree your work - 6.25 - -

requirements with appropriate people

PC2. keep your immediate work area 6.25 6.25 - -

clean and tidy

PC3. utilize your time effectively 6.25 6.25 - -

PC4. use resources correctly and 6.25 12.5 - -

efficiently

PC5. treat confidential information - 6.25 - -

correctly

PC6. work in line with your organizations - 12.5 - -

policies and procedures

PC7. work within the limits of your job role - 6.25 - -

PC8. obtain guidance from appropriate - 6.25 - -

people, where necessary

PC9. ensure your work meets the agreed 6.25 12.5 - -

requirements

NOS Total 25 75 - -


Qualification Pack


NOS Code SSC/N9001

NOS Name Manage your work to meet requirements

Sector IT-ITeS

Sub-Sector IT Services

Primary Occupation Across all occupations


NSQF Level 4

Credits TBD

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Qualification Pack

SSC/N9002: Work effectively with colleagues

Description

This unit is about working effectively with colleagues, either in your own work group or in other work

groups within your organization.

Scope


• Communicate with colleagues • Show respect


To be competent, the user/individual on the job must be able to: Communicate with colleagues

PC1. communicate with colleagues clearly, concisely and accurately

PC2. work with colleagues to integrate the work effectively with theirs PC3. pass on essential information to colleagues in line with organizational requirements

Show respect

PC4. work in ways that show respect for colleagues PC5. carry out commitments one has made to colleagues PC6. identify any problems while working with colleagues and take the initiative to solve these

problems PC7. follow the organizations policies and procedures for working with colleagues

Knowledge and Understanding (KU) The individual on the job needs to know and understand:

KU1. the organizations policies and procedures for working with colleagues and the role and

responsibilities in relation to this KU2. the importance of effective communication and establishing good working relationships with

colleagues KU3. different methods of communication and the circumstances in which it is appropriate to use

these KU4. benefits of developing productive working relationships with colleagues KU5. the importance of creating an environment of trust and mutual respect in an environment

where there is no authority over those working with KU6. where do not meet the commitments, the implications this will have on individuals and the

organization KU7. different types of information that colleagues might need and the importance of providing this

information when it is required KU8. the importance of understanding problems from the colleagues perspective and how to

provide support, where necessary, to resolve these


Qualification Pack

Generic Skills (GS)


GS1. complete accurate, well written work with attention to detail

GS2. communicate effectively with colleagues in writing GS3. read instructions, guidelines, procedures, rules and service level agreements

GS4. listen effectively and orally communicate information accurately GS5. ask for clarification and advice from line managers

GS6. make decisions on suitable courses of action GS7. plan and organize the work to achieve targets and deadlines GS8. ensure the work meets customer requirements, and deliver consistent and reliable service GS9. apply problem solving approaches in different situations GS10. apply balanced judgments to different situations GS11. ensure the work is complete and free from errors GS12. get the work checked by peers GS13. work effectively with colleagues and other teams in a team environment GS14. treat other cultures with respect GS15. identify and refer anomalies GS16. help reach agreements with colleagues GS17. keep up to date with changes, procedures and practices in the role


Qualification Pack

Assessment Criteria



20 80 - -

PC1. communicate with colleagues clearly, - 20 - -

concisely and accurately

PC2. work with colleagues to integrate your - 10 - -

work effectively with theirs

PC3. pass on essential information to

20 - - - colleagues in line with organizational

requirements

PC4. work in ways that show respect for - 20 - -

colleagues

PC5. carry out commitments you have made - 10 - -

to colleagues

PC7. identify any problems you have working

- 10 - - with colleagues and take the initiative to solve

these problems

PC8. follow the organizations policies and - 10 - -

procedures for working with colleagues

NOS Total 20 80 - -


Qualification Pack


NOS Code SSC/N9002

NOS Name Work effectively with colleagues

Sector IT-ITeS




NSQF Level 4

Credits TBD

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Qualification Pack

SSC/N9004: Provide data/information in standard formats

Description

This unit is about providing specified data/information related to your work in templates or other standard

formats.

Scope

This unit/task covers the following: • Obtain information

• Analyze and report information


To be competent, the user/individual on the job must be able to: Obtain information

PC1. establish and agree with appropriate people the data/information you need to provide, the

formats in which you need to provide it, and when you need to provide it PC2. obtain the data/information from reliable sources PC3. check that the data/information is accurate, complete and up-to-date PC4. obtain advice or guidance from appropriate people where there are problems with the

data/information

Analyze and report information PC5. carry out rule-based analysis of the data/information, if required

PC6. insert the data/information into the PC7. report any unresolved anomalies in the data/information to appropriate people PC8. provide complete, accurate and up-to-date data/information to the appropriate people in the

required formats on time



KU1. organizations procedures and guidelines for providing data/information in standard

formats and your role and responsibilities in relation to this

KU2. the knowledge management culture of your organization

KU3. organizations policies and procedures for recording and sharing information and the

importance of complying with these

KU4. the importance of validating data/information before use and how to do this

KU5. procedures for updating data in appropriate formats and with proper validation

KU6. the purpose of the CRM database

KU7. how to use the CRM database to record and extract information

KU8. the importance of having your data/information reviewed by others

KU9. the scope of any data/information requirements including the level of detail required

KU10. the importance of keeping within the scope of work and adhering to timescales


Qualification Pack

KU11. data/information one may need to provide including the sources and how to do this

KU12. templates and formats used for data/information including their purpose and how to use

these KU13. the techniques used to obtain data/information and how to apply these KU14. how to carry out rule-based analysis on the data/information KU15. typical anomalies that may occur in data/information KU16. whom to go to in the event of inaccurate data/information and how to report this

Generic Skills (GS)


GS1. complete accurate, well written work with attention to detail

GS2. read instructions, guidelines, procedures, rules and service level agreements

GS3. listen effectively and orally communicate information accurately GS4. follow rule-based decision-making processes

GS5. make decisions on suitable courses of action GS6. plan and organize the work to achieve targets and deadlines GS7. check the work meets customer requirements and exceed customer expectations GS9. apply problem solving approaches in different situations GS10. configure data and disseminate relevant information to others GS11. apply balanced judgments to different situations

GS12. use information technology effectively, to input and/or extract data accurately

GS13. validate and update data

GS14. store and retrieve information IT-ITeS Sector Skill Council 36

Qualification Pack

Assessment Criteria



25 75 - -

PC1. establish and agree with appropriate people the data/information you need to

12.5 - - - provide, the formats in which you need to

provide it, and when you need to provide it

PC2. obtain the data/information from reliable - 12.5 - -

sources

PC3. check that the data/information is 6.25 6.25 - -

accurate, complete and up-to-date

PC4. obtain advice or guidance from

- 12.5 - - appropriate people where there are problems

with the data/information

PC5. carry out rule-based analysis of the - 25 - -

data/information, if required

PC6. insert the data/information into the - 12.5 - -

PC7. report any unresolved anomalies in the 6.25 - - -

data/information to appropriate people

PC8. provide complete, accurate and up-to-date

- 6.25 - - data/information to the appropriate people in

the required formats on time

NOS Total 25 75 - -


Qualification Pack


NOS Code SSC/N9004

NOS Name Provide data/information in standard formats

Sector IT-ITeS




NSQF Level 4

Credits TBD

Version 2.0





Qualification Pack

SSC/N9006: Build and Maintain relationships in a Workplace

Description

This unit is about building and maintaining constructive relationships at the workplace.

Scope

This unit/task covers the following: Build relationships Maintain relationships Appropriate people: line

manager, members of the team/department, members from other teams/departments

Build relationships

Maintain relationships


Build relationships To be competent, the user/individual on the job must be able to:

PC1. build rapport with appropriate people at the workplace

PC2. develop new professional relationships PC3. build alliances to establish mutually beneficial working arrangements

PC4. foster an environment where others feel respected PC5. identify and engage a diverse range of influential contacts Maintain relationships To be competent, the user/individual on the job must be able to:

PC6. obtain guidance from appropriate people, where necessary PC7. attentively listen to ideas and give constructive feedback PC8. promptly resolve conflicts between team members PC9. work with colleagues to deliver shared goals PC10. recognize the contributions made by colleagues



KU1. organizational policies and procedures for building relationships and their role and

responsibilities in relation to this KU2. different training programs to enable the development of relevant behavioural competencies

KU3. the importance of creating an environment of trust and mutual respect in the organisation KU4. the importance of effective communication in developing productive working relationships

with colleagues KU5. different types of information that colleagues might need and the importance of providing this

information when it is required


Qualification Pack

Generic Skills (GS) User/individual on the job needs to know how to:

GS1. ask for clarification and advice from line managers

GS2. work effectively in a team environment


Qualification Pack

Assessment Criteria



Build relationships 17 33 - -

PC1. build rapport with appropriate people at 3 7 - -

the workplace

PC2. develop new professional relationships 3 7 - -

PC3. build alliances to establish mutually 3 7 - -

beneficial working arrangements

PC4. foster an environment where others 4 6 - -

feel respected

PC5. identify and engage a diverse range of 4 6 - -

influential contacts

Maintain relationships 13 37 - -

PC6. obtain guidance from appropriate 3 7 - -

people, where necessary

PC7. attentively listen to ideas and give 3 7 - -

constructive feedback

PC8. promptly resolve conflicts between 2 8 - -

team members

PC9. work with colleagues to deliver shared 2 8 - -

goals

PC10. recognize the contributions made by 3 7 - -

your colleagues

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N9006

NOS Name Build and Maintain relationships in a Workplace

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

SSC/N9007: Build and Maintain client satisfaction

Description

This unit is about building and maintaining satisfaction with clients

Scope

This unit/task covers the following: Define client requirements Ensure client satisfaction Clients: internal,

external

Define client requirements

Ensure client satisfaction


Define client requirement To be competent, the user/individual on the job must be able to:

PC1. gather the client context and requirements PC2. manage fluctuating client priorities and expectations Ensure client satisfaction To be competent, the user/individual on the job must be able to:

PC3. respond to requests in a timely and accurate manner PC4. continuously improve service based on client feedback PC5. plan deliverables based on client needs



KU1. organizational policies and procedures for working with clients and their role and

responsibilities in relation to this KU2. the importance of effective communication and establishing good working relationships with

colleagues KU3. methods of communication and the circumstances in which it is appropriate to use these KU4. types of information that clients might need and the importance of providing this information

when it is required IT-ITeS Sector Skill Council 43

Qualification Pack

Generic Skills (GS)


GS1. communicate effectively with clients in writing

GS2. follow instructions, guidelines, procedures, rules and service level agreements

GS3. check that self/peers work meets customer requirements

GS4. deliver consistent and reliable service to customers

GS5. apply balanced judgments to different situations


Qualification Pack

Assessment Criteria



Define client requirement 15 25 - -

PC1. gather the client context and 5 10 - -

requirements

PC2. manage fluctuating client priorities 10 15 - -

and expectations

Ensure client satisfaction 15 45 - -

PC3. respond to requests in a timely and 5 15 - -

accurate manner

PC4. continuously improve service based - 15 - -

on client feedback

PC5. plan deliverables based on client 10 15 - -

needs

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N9007

NOS Name Build and Maintain client satisfaction

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

SSC/N9010: Convince others to take appropriate action in different

situations

Description

This unit is about convincing others to take appropriate action in different situations.

Scope

This unit/task covers the following: Define needs Persuade others Range: Appropriate people such as line

manager, members of the team/department, members from other teams / departments

Define needs

Persuade others


Define needs To be competent, the user/individual on the job must be able to:

PC1. gather needs of concerned people PC2. adapt arguments to consider diverse needs Persuade others To be competent, the user/individual on the job must be able to:

PC3. use small wins as milestones to gain support for ideas PC4. persuade with the help of concrete examples or evidences PC5. take defined steps to reach a consensus on the course of action



KU1. organizational policies and procedures for persuading people and their role and

responsibilities in relation to this KU2. types of information that people might need and the importance of providing this information

when it is required KU3. methods of communication and the circumstances in which it is appropriate to use these

Generic Skills (GS)


GS1. ask for clarification and advice from appropriate people

GS2. listen effectively and orally communicate information accurately GS3. make decision on a suitable course of action GS4. apply balanced judgments to different situations


Qualification Pack

Assessment Criteria



Define needs - 25 - -

PC1. gather needs of concerned people - 10 - -

PC2. adapt arguments to consider - 15 - -

diverse needs

Persuade others 30 45 - -

PC3. use small wins as milestones to gain 10 15 - -

support for ideas

PC4. persuade with the help of concrete 10 15 - -

examples or evidences

PC5. take defined steps to reach a 10 15 - -

consensus on the course of action

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N9010

NOS Name Convince others to take appropriate action in different situations

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

SSC/N9014: Maintain an inclusive, environmentally sustainable

workplace.

Description

The unit is about implementing and improving diversity equality and inclusion in a sustainable and

environment friendly workplace.

Scope

This unit/tasks covers the following: Enrich policies to respect diversity; Reinforce practices/

regulations/policies to promote and improve equity (equality)/inclusivity; Emphasize sustainable

environmental practices.


To be competent, the user/individual on the job must be able to:

Element 1 – Sustainable Practices

PC1: optimize usage of electricity/energy, materials, and water in various tasks/activities/processes and

plan the implementation of energy efficient systems in a phased manner.

PC2: Segregate recyclable, non-recyclable and hazardous waste generated for disposal or efficient

waste management.

Element 2 – Respect diversity and strengthen practices to promote equity (equality)/inclusivity PC3: Understand the diversity policy of the organization and use internal & external communication to

colleagues to improve.

PC4: Comply with PwD inclusive policies for an adaptable and equitable work environment. PC5: Improve through specifically designed recruitment practices, PwD friendly infrastructure, job roles,

etc. PC6: Use and advocate for appropriate verbal/nonverbal communication, schemes and benefits of

PwD.



KU1. the organization’s policies and procedures about gender inclusivity, equality and sustainability

while working with colleagues and your role and responsibilities in relation to this.

KU2. inclusive tools and practices of communication to acknowledge/validate, share and promote the cause of gender parity at workplace. For example - supporting women with mentorship programs. speaking out against discriminatory practices or harassment.


Qualification Pack

KU3. the concept of gender, gender equality and gender discrimination, and all forms of gender

discrimination, violence and inequality, including the current and historical causes of gender

inequality in the workplace.

KU4. how to maintain and provide a conducive work environment that is free from any harassment;

facilities and amenities to PwD to perform and excel in their role.

KU5. organization’s redressal mechanisms (like the POSH committee) to address harassment and

bias at the workplace, with awareness of prevalent legislations against bias and sexual

harassment.

KU6. initiatives towards efficient use of natural resources and energy, reduction and prevention of

pollution and promoting waste avoidance and recycling measures in line with internationally

disseminated technologies and practices.

KU7. knows all about various energy options including renewable and non-renewable with their

environmental impacts, health issues, usage, safety and energy security.

KU8. implications that any non-compliance with electricity and energy may have on individuals and the

organization.

KU9. know organization’s electricity first aid emergency procedures.

KU10. monitoring, measuring and reporting performance of environmental conservation.

KU11. different types of electricity accidents, safety and security and how and when to report these.

KU12. how to use the electricity/energy safety, accident reporting, emergency procedures and the

importance of these.

Generic Skills (GS)


GS1. Read PwD instructions, guidelines, procedures, diversity policies/acts, rules and service level agreements.

GS2. Aware of one’s own gender identity and gender role; and respectful of the gender performances of others.

GS3. Organize team building or sensitization workshops to address gender biases, stereotypes and

potentially blind spots. GS4. Clarify personal norms and values related to energy production and usage as well as to reflect

and evaluate their own energy usage in terms of efficiency and sufficiency. GS5. Listen and communicate (oral) effectively and accurately on all PwD policies. GS6. Apply balanced judgments in gender diversity situations. GS7. Take action to reduce the carbon footprint of business activities and embed environmental

responsibility

GS8. Calibration session with employees to discuss gender biases, stereotypes and potentially blind

spots.


Qualification Pack

Assessment Criteria



To be competent, the user/individual on the job must 20 80 - -

be able to:

PC1: Optimize usage of electricity/energy, materials, and water in various tasks/activities/processes and plan the implementation of energy efficient systems in a phased manner.

5 15 - -

PC2: Segregate recyclable, non-recyclable and hazardous waste generated for disposal or efficient waste management

5 15 - -

PC3: Understand the diversity policy of the organization and use internal & external communication to colleagues to improve

5 10 - -

PC4: Comply with PwD inclusive policies for an adaptable and equitable work environment.

0 10 - -

PC5: Improve through specifically designed recruitment practices, PwD friendly infrastructure, job roles, etc.

- 20 - -

PC6: Use and advocate for appropriate verbal/nonverbal communication, schemes and benefits of PwD.

5 10 - -

NOS Total 20 80 - -


Qualification Pack


NOS Code SSC/N9014

NOS Name Maintain an inclusive, environmentally sustainable workplace

Sector IT-ITeS

Sub-Sector IT Services, Business Process Management, Engineering R&D, Software

Product Development

Primary Occupation Generic


NSQF Level 4

Credits TBD

Version 2.0





Qualification Pack

SSC/N8106: Evaluate risk of deploying algorithmic models

Description

This unit is about evaluating the risks in deploying algorithmic models and developing mitigation measures for

internal and external clients

Scope

This unit/task covers the following: Define model scope Analys ealgorithmic model Range: Risks such as

accidental or intentional biases, errors, frauds

Define model scope

Analyse algorithmic model


Define model scope To be competent, the user/individual on the job must be able to:

PC1. define the purpose and metrics for the algorithmic model PC2. define data sources used to design the model and data flows used to reinforce the model PC3. define and evaluate the assumptions used while designing the algorithmic model PC4. evaluate the range of expected outcomes of the algorithmic model Analyse algorithmic model To be competent, the user/individual on the job must be able to:

PC5. test the model with different inputs and identify the factors that are creating a deviation

from the expected outcomes PC6. estimate the risks involved in case the algorithmic model deviates from the expected

outcomes PC7. introduce checks and mitigation measures for each of the potential risks resulting from the

model PC8. create documentation on potential risks and the associated mitigation measures

PC9. validate risks and mitigation measures with appropriate stakeholders PC10. recommend and implement corrective actions to the model as required

PC11. evaluate the model for all possible use cases/scenarios



KU1. the purpose and aims of the analysis being undertaken

KU2. organizational policies, procedures and guidelines which relate to evaluating risks associated

with algorithmic models and documenting model risks and mitigation measures KU3. data sources and how to access documents and information from data sources

KU4. organizational policies and procedures for sharing data


Qualification Pack

KU5. whom to involve when evaluating risk and recommending mitigations KU6. the range of standard templates and tools available and how to use them KU7. use cases and the suitability of various algorithmic models to address them KU8. factors that contribute to risks. For example: outdated, irrelevant or biased input data

insufficient sample sizes flawed design logic, coding errors etc. KU9. different mitigation measures along areas such as data selection, algorithm design, live use in

production etc. KU10. identification of anomalies in data KU11. various operating systems such as linux, ubuntu, or windows

Generic Skills (GS)


GS1. follow rule-based decision-making processes

GS2. make a decision on a suitable course of action GS3. analyze data and activities GS4. evaluate impact analysis of the various actions performed and disseminate relevant



Qualification Pack

Assessment Criteria



Define model scope 12 28 - -

PC1. define the purpose and metrics for the 3 7 - -

algorithmic model

PC2. define data sources used to design the

3 7 - - model and data flows used to reinforce the

model

PC3. define and evaluate the assumptions used 3 7 - -

while designing the algorithmic model

PC4. evaluate the range of expected outcomes 3 7 - -

of the algorithmic model

Analyse algorithmic model 18 42 - -

PC5. test the model with different inputs and

3 7 - - identify the factors that are creating a deviation

from the expected outcomes

PC6. estimate the risks involved in case the

8 12 - - algorithmic model deviates from the expected

outcomes

PC7. introduce checks and mitigation measures

5 10 - - for each of the potential risks resulting from the

model

PC8. create documentation on potential risks - 5 - -

and the associated mitigation measures

PC9. validate risks and mitigation measures - 2 - -

with appropriate stakeholders

PC10. recommend and implement corrective - 3 - -

actions to the model as required

PC11. evaluate the model for all possible use 2 3 - -

cases/scenarios

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8106

NOS Name Evaluate risk of deploying algorithmic models

Sector IT-ITeS




NSQF Level 7

Credits TBD

Version 2.0





Qualification Pack

SSC/N8107: Evaluate business performance of algorithmic models

Description

This unit is about evaluating the performance of deployed algorithmic models at meeting expected

business outcomes.

Scope

This unit/task covers the following: Define performance metrics Perform analysis on model performance Range: Optimization techniques such as mini-batch gradient descent,momentum, RMSprop, Adam,

Bayesian optimization, grid search, ridge regression

Define performance metrics

Perform analysis on model performance


Define performance metrics To be competent, the user/individual on the job must be able to:

PC1. identify the objective being addressed by the model PC2. define suitable evaluation criteria and metrics to evaluate model performance as per objective Perform analysis on model performance To be competent, the user/individual on the job must be able to:

PC3. evaluate the performance of the algorithmic model PC4. identify the hyperparameters to maximize model performance

PC5. test different hyperparameter configurations PC6. use best-fit hyperparameter configuration to maximize model performance




KU2. organizational policies, procedures and guidelines which relate to evaluating business

performance of algorithmic models

KU3. different data sources and how to access documents and information

KU4. organizational policies and procedures for sharing data

KU5. who to involve when evaluating performance of algorithmic models

KU6. the range of standard templates and tools and how to use them

KU7. performance metrics to monitor business outcomes of algorithmic models

KU8. methodological approaches for identifying model hyperparameters such as grid

search, random search, Bayesian optimization

KU9. how to tune hyperparameter configurations

KU10. Identification of anomalies in data


Qualification Pack

KU11. operating systems such as linux, ubuntu, or windows

Generic Skills (GS)





Qualification Pack

Assessment Criteria



Define performance metrics 6 14 - -

PC1. identify the objective being addressed 3 7 - -

by the model

PC2. define suitable evaluation criteria and

3 7 - - metrics to evaluate model performance as

per objective

Perform analysis on model performance 24 56 - -

PC3. evaluate the performance of the 6 14 - -

algorithmic model

PC4. identify the hyperparameters to 6 14 - -

maximize model performance

PC5. test different hyperparameter 6 14 - -

configurations

PC6. use best-fit hyperparameter

6 14 - - configuration to maximize model

performance

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8107

NOS Name Evaluate business performance of algorithmic models

Sector IT-ITeS




NSQF Level 7

Credits TBD

Version 2.0





Qualification Pack

SSC/N8108: Define business outcomes and create visualizations from

results of the analysis

Description

This unit is about defining business outcomes from results of a statistical analysis and create visualizations to

report them.

Scope

This unit/task covers the following: Define the scope Report business outcomes Range: Graphical formats

such as pie charts, line graphs, scatter graphs, bar charts, column graphs, ring plots. Types of analysis such

as trend, moving average, regression, inferential, exploratory, predictive, confirmatory correlation,

association, forecasting, estimation, cluster, trend plotting


Define the scope To be competent, the user/individual on the job must be able to:

PC1. identify the objective of the analysis PC2. establish the purpose, scope, and target audience to report the business outcomes PC3. define the delivery mode and format (such as excel sheets, reports, APIs) to report the

business outcomes Report business outcomes To be competent, the user/individual on the job must be able to:

PC4. summarize the defined business outcomes into a narrative PC5. select suitable visualizations to represent the defined business outcomes PC6. present outcomes through visualizations using standard templates and agreed language

standards PC7. validate visualizations with appropriate people PC8. publish visualizations for consumption across all agreed formats




KU2. organizational policies, procedures and guidelines which relate to creating visualizations KU3. different data sources and how to access documents and information from data sources KU4. organizational policies and procedures for sharing data

KU5. who to involve when defining business outcomes and creating visualizations

KU6. intended audiences for reporting business outcomes KU7. their organization's knowledge base and how to access and update this KU8. organizational processes and procedures for approving and publishing documents


Qualification Pack

KU9. the range of standard templates and tools available and how to use these

KU10. statistical concepts such as distributions, hypothesis testing, confidence intervals etc. KU11. how to evaluate results of quantitative or qualitative analysis to define business outcomes

KU12. graphical formats for presenting data and how to create these KU13. styles used in visualizations, including your organizations house style, types & templates KU14. applications, libraries or packages to create visualizations using tools such as Tableau,

Qlikview, d3js etc KU15. change management procedures, including version control and approvals

KU16. identification of anomalies in data KU17. various operating systems such as linux, ubuntu, or windows

Generic Skills (GS)


GS1. complete accurate well written work with attention to detail

GS2. follow instructions, guidelines, procedures, rules and service level agreements GS3. check that your own and/or your peers work meets customer requirements GS4. work effectively in a customer facing environment GS5. analyze data and activities GS6. evaluate business impact and disseminate relevant information to others

GS7. check the work completion without errors


Qualification Pack

Assessment Criteria



Define the scope 15 30 - -


PC2. establish the purpose, scope, and target 5 10 - -

audience to report the business outcomes

PC3. define the delivery mode and format

5 10 - - (such as excel sheets, reports, APIs) to report

the business outcomes

Report business outcomes 15 40 - -

PC4. summarize the defined business 2 8 - -

outcomes into a narrative

PC5. select suitable visualizations to 3 7 - -

represent the defined business outcomes

PC6. present outcomes through visualizations

10 15 - - using standard templates and agreed

language standards

PC7. validate visualizations with appropriate - 5 - -

people

PC8. publish visualizations for consumption - 5 - -

across all agreed formats

NOS Total 30 70 - -


Qualification Pack


NOS Code SSC/N8108

NOS Name Define business outcomes and create visualizations from results of the

analysis

Sector IT-ITeS




NSQF Level 6

Credits TBD

Version 2.0





Qualification Pack

Assessment Guidelines and Assessment Weightage

Assessment Guidelines

1. Criteria for assessment for each Qualification Pack will be created by the Sector Skill Council. Each

Performance Criteria (PC) will be assigned marks proportional to its importance in NOS. SSC will also

lay down proportion of marks for Theory and Skills Practical for each PC.

2. The assessment for the theory part will be based on knowledge bank of questions created by the

SSC.

3. Assessment will be conducted for all compulsory NOS, and where applicable, on the selected

elective/option NOS/set of NOS.

4. Individual assessment agencies will create unique question papers for theory part for each

candidate at each examination/training center (as per assessment criteria below).

5. Individual assessment agencies will create unique evaluations for skill practical for every student at

each examination/training center based on this criterion.

6. To pass a QP, a trainee should score an average of 70% across generic NOS’ and a minimum of

70% for each technical NOS

7. In case of unsuccessful completion, the trainee may seek reassessment on the Qualification Pack.

Recommended Pass % : 70

Assessment Weightage

Compulsory NOS

National Occupational Theory Practical Project Viva Total Weightage

Standards Marks Marks Marks Marks Marks

SSC/N8101.Import Data as 30 70 - - 100 9

per specifications

SSC/N8102.Preprocess data 30 70 - - 100 9

as per specifications

SSC/N8103.Perform

30 70 - - 100 9 exploratory data analysis as

per specifications


Qualification Pack



SSC/N8105.Apply pre-

30 70 - - 100 8 designed algorithmic models

to specified use cases

SSC/N8104.Perform research

28 72 - - 154 8 and design of algorithmic

models

SSC/N9001.Manage your 25 75 - - 100 5

work to meet requirements

SSC/N9002.Work effectively 20 80 - - 100 5

with colleagues

SSC/N9004.Provide

25 75 - - 100 5 data/information in standard

formats

SSC/N9006.Build and

30 70 - - 100 5 Maintain relationships in a

Workplace

SSC/N9007.Build and 30 70 - - 100 5

Maintain client satisfaction

SSC/N9010.Convince others

30 70 - - 100 4 to take appropriate action in

different situations

SSC/N9014. Maintain an inclusive, environmentally sustainable workplace

20 80 - - 100 4

Total 328 872 - - 1200 76


Qualification Pack

Elective: 1 Model Risk Assessment



SSC/N8106.Evaluate risk

30 70 - - 100 24 of deploying algorithmic

models

Total 30 70 - - 100 24

Elective: 2 Model Business Performance



SSC/N8107.Evaluate

30 70 - - 100 24 business performance of

algorithmic models

Total 30 70 - - 100 24

Elective: 3 Visualizations



SSC/N8108.Define business outcomes and

30 70 - - 100 24 create visualizations from

results of the analysis

Total 30 70 - - 100 24


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