master open day nov 2017 - business analytics and operations research
Post on 22-Jan-2018
52 Views
Preview:
TRANSCRIPT
Nikki Donkers
Program Coordinator
MSc EME
MSc BAOR
MSc QFAS
Juan Vera
Academic Director Msc BAOR
Associate Professor Operations Research
Meet the team
4
Our Focus
“Soft” skills, crucial for the successful
implementation of business projects
• presenting for high impact
• Project & team setup
Theory and state of the art
methods to solve complex
business problems
• analysing big data, and/or
making predictions
• optimization
“Hard” skills needed in practice:
• translating the problem into a
mathematical model
• choosing the right solution
method
• using or developing relevant
computer software
Smarter decision making using math and data
BAOR in Tilburg
5
• Modern program including Data Science methods
• Quality of teachers:• World class researchers in BAOR / Strong connection to practice
• Part of big JADS initiative
• Extensive company network
• Wide variety of applications and job opportunities
• Improving society using math and data
• Many, many job opportunities...!
Master program structure (1 year)
6
4 electives
5 Compulsory courses
(out of 6):
• Core of the program
• Knowledge that
everyone should
possess
2 Electives
(out of many):
• Freedom to specialize
further
• Econometrics, Marketing,
Economics, Finance, Math
• Make it your program(!)
Master Thesis:
• Novel contribution
• Usually within an
internship
• Real experience!
8
Data Science Methods
Goals:
• Acquire knowledge of theory, methods and
techniques, to analyze big data sets.
• Acquire the skills necessary to implement
these in practical cases (incl. software).
Contents:
• Supervised vs. unsupervised learning
• Loading + cleaning data
• Visualizing data + dimension reduction
• Classification (discriminant analysis, nearest neighbor, logistic regression
• Resampling methods (cross-validation, bootstrap)
• Model selection (forward selection, lasso, shrinkage, principal components)
• Tree-based classification (regression trees, bagging, boosting)
• Support Vector Machines (support vector classifiers)
• Applications
9
Professional Business Analytics Skills
Goals:
• Acquire those softer skills that are
essential for an analytics professional
Contents:
• How to ‘sell’ business analytics?
• Project & team setup
• Data preparation, cleansing & visualization
• Modeling the essence
• Validation
• Change management
• Presenting for high impact
• …
• Business analytics is a process; not a single analysis
10
Decision Making with Business Analytics
Goals:
• Holistic view on Business Analytics.
• Advanced BA models/methods for
Decision Making.
• State-of-the art BA software.
Contents:
• Decision making under uncertainty
• Prescriptive analytics:
• Issues of scale I: Prescriptive analytics on huge data sets;
• Skill or luck: Analyzing performance in a random environment;
• Text as data: Text mining and sentiment analysis.
• Predictive analytics:
• Simulation and risk analysis: Evaluating risk on complex systems;
• Issues of scale II: Finding large scale analytics models, optimization issues;
• Important modelling issues, validation / verification, and the Impact of Big Data.
Electives
11
• The remaining core course
• Finance Analytics :
• Asset Liability Management
• Marketing Analytics:
• Customer Analytics
• Market assessment
• Econometrics and Mathematical
Economics:
• Core courses of the MSc
EME
• Business Analytics:
• Business Analytics & Emerging
Trends
• LNMB courses (only MSc and not
PhD level):
• Scheduling
• Advanced Linear Programming
• Queueing Theory
• Discrete Optimization
Schedule: February entry point
12
Master
Thesis
Professional Business Analytics
SkillsData Science
2 ENTRY POINTS: September and February
Unit 1 (Aug -
Oct)Unit 2 (Oct - Dec) Unit 3 (Jan -
Mar)
Unit 4 (Mar -
Jun)
SimulationDecision
Making
with Buss. Anal.
Optimization
Supply Chain
Analytics
Elective
Elective
Schedule: September entry point
13
Master
Thesis ?
Data Science
2 ENTRY POINTS: September and February
Unit 1 (Aug -
Oct)Unit 2 (Oct - Dec) Unit 3 (Jan -
Mar)
Unit 4 (Mar -
Jun)
Simulation
Master
Thesis
Decision
Making
with Buss. Anal.
Optimization
Elective
Elective
Supply Chain
Analytics
Optimal cancer treatment
15
Frank Steenbergen
Objective
Find optimal radiation plan such that
- tumor is targeted
- healthy organs are spared
Techniques
Nonlinear and robust optimization
Optimal food supply for hungry people
16
Koen Peters
Riley Badenbroek
Objective
Find optimal food supply plan such that
- daily meals satisfy nutritional requirements
- total logistics costs are minimized
Techniques
Mixed integer linear optimization, conic optimization, robust
Optimal flood protection
17
Chris Pustjens
Objective
Find optimal set of flood protection measures such that
- safety norms are satisfied
- total costs are minimized
Techniques
Integer optimization, shortest path, predictive analytics
Optimal shift planning of Air Traffic Controllers
18
Dori van Hulst
Objective
Find optimal shift planning such that
- all types of restrictions are satisfied
- total costs of under- and overcapacity are minimized
Techniques
Mixed integer optimization, robust optimization
Optimal manpower planning
19
Eline Slijkhuis
Objective
Find optimal manpower planning such that
- all types of restrictions are satisfied
- total contract costs are minimized
Techniques
Mixed integer optimization, predictive analytics
Big data for network optimization
20
Ioannis Zempekakis
Objective
How to use Big Data in facility location optimization?
Techniques
Predictive analytics, Big Data techniques
Mixed Integer Optimization
Optimal refinery planning
21
Harmen Boersma
Objective
Find production plan such that
- all types of restrictions are satisfied
- profit is maximized
Techniques
Nonconvex optimization
Optimal energy planning in Smart Grids
22
Robin Swinkels
Objective
Find optimal production/storage plan such that
- demand of heat/gas can be satisfied
- total costs are minimized
Techniques
Linear optimization, robust optimization, predictive analytics
Job opportunities
A lot of opportunities:
• Consultant at a BA/OR center or department of a large firm
• Management consulting
• Management support (manufacturing, service)
• Application providers (SAP, Quintiq, etc.)• Application builders• Solution builders• Implementers
• Research institutes (TNO, Deltares, …)
23
Job opportunities in academia
• PDEng program “Data Science”
• 2 years, with salary
• Joint program with TU/e
• In monastery “Marienburg”, Den Bosch
• Getting a PhD
• 2nd year of Research Master program
• 3 years PhD
24
Job descriptions
26
Some job descriptions of recent graduates:
Supply Chain Consultant OM Partners
Implementation Consultant ORTEC
Life Cycle Management Analyst Philips Healthcare
Optimization Algorithm Expert Quintiq
Quantitative Analyst Rabobank Nederland
Quantitative Researcher Robeco
Consultant Quintiq
Supply Chain Consultant ORTEC
Risk Manager Cardano
Supply Chain Specialist Bavaria
Consultant Fabory Group
Data Scientist Greenhouse
OR Specialist Dutch Railways
Consultation for CV and job-
applicationsIndividual guidance
Training, courses & workshops
Career events
Student Career Services and ASSET Econometrics offer
Available at information fair!
We help you on your way
Application deadlines vary (2 entry points: Dutch, EEA & NON-
EEA)
We offer SCHOLARSHIPS, see webpage
We REPLY IN 2-3 WEEKS after you apply to our program
Tilburg University students: BA Econometrics
Other university students: Any BA with Strong Math/OR
background
Premaster option: If insufficient
background,
max 5 Pre-Master coursesSee https://www.tilburguniversity.edu/education/masters-programmes/econometrics/application/ for specific requirements!
Admissions
Register in Studielink for:
Operations Research / Management Science
top related