Predictive Analytics Innovation

Gain greater insight with Predictive Analytics

February 12 & 13, 2015The Westin, San Diego, CA

Confirmed Speakers

Confirmed Speakers• Chief Data Scientist, Dell

• Lead Research Scientist, eBay

• Director, Data Architecture, Walgreens

• Research Scientist, Amazon

• Data Scientist, Sharp Labs

• Chief Data Scientist, Ranker

• Director, People Analytics, Walmart

• Data Scientist, Rdio

• Staff Data Scientist, Linkedin

• Head of Fraud Data & Analytics, TD Bank

• Senior Staff Data Scientist, Twitter

• CDO, 58.com

• Director, Data Science, Buzzfeed

• Head of Analytics, Poshmark

• Producer, Data for Good

• People Scientist, Google

• Data Scientist, Facebook

• Director, Analytics, Scotts Miracle-Gro

• Chief Data Scientist, Mashable

• Senior Director, Strategy, Slacker Radio

• Director, Data Science, CHEGG

• Director, Market Analytics, eBay

• VP, Global Reporting & Analytics, Sony

• Chief Architect, StubHub

• Product Manager, LinkedIn

• Director, Product Analytics, Data Science

& Engineering, Netflix

• Chief Data Scientist, Banjo

• Data Scientist, Foursquare

• Game Product Analyst, Facebook

• Software Engineer, Twitter

Delegates include• VP, Pricing & Promotions - AutoTrader.com

• Director, Digital Analytics - Salesforce.com

• Technical Leader - Ford Motor Company

• VP, Customer Intelligence & CI - Coach

• Director, Marketing Analytics - Verizon Wireless

• Analytics Specialist - Nike

Who Will You Meet?There is no question that IE. provides the gold standard events in the industry and will connect you with decision makers within the analytics industry. You will be meeting senior level executives from major corporations and innovative small to medium size companies.

Job Title Of Attendees

President/Principal

SVP/VP

C-Level

Snr. Director/Director

Global Head/ Head

Snr. Manager/Manager

Academic (1%)

78%

1000+ Employees300-999 Employees50-299 EmployeesLess than 49 Employees

Company Size Of Attendees

8%

11%

25%56% 81%Attendees are

companies with at least 300

employees

3%

21%

12%

42%

13%

8%

Attendees are at Director level or above

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About the SummitThe Predictive Analytics Innovation Summit returns to San Diego this February for what promises to be this year’s leading event for analytics practitioners to discuss how they are making the most of their data through the use of data analytics.

The explosion of Big Data of recent years - and the growth of the web and mobile as platforms creating large amounts of data - has created the opportunity for businesses to invest in analytics and data science in order to drive success across all areas of operation. Big Data offers a vast resource for businesses to capitalize on: it is through data analytics that this resource can offer real value.

The mass shift away from instinct-driven decision-making towards an approach that makes use of both quantitative and qualitative insight has been made possible through investment in analytics, and companies must now invest in analytics to inform the decision-making process or risk being left behind. Data-driven decision-making is essential for organizations looking to gain greater insight into customers and competitors while simultaneously maximizing profits and minimizing loss.

Join us in San Diego this February to hear how innovative approaches using analytics are changing the business landscapes both for multinational corporations and start-ups.

Speaker Information

Karthik Ramasamy is a Staff Data Scientist @ LinkedIn Security, keeping the site secure against fraud and abuse by malicious users and botnets. He is also responsible for Hadoop data security and teaches Hive to product managers. He earned CS Master's from Columbia university, specializing in Machine Learning.

Democratizing Hadoop

LinkedIn has several petabytes of data stored in multiple hadoop clusters. This talk explores how LinkedIn enables employees with diverse background, from customer support professionals to data scientists, to access this big data, and how security plays a huge role in democratizing Hadoop. We’ll also explore open source and commercial tools used by LinkedIn, as well as other publicly available tools, which enable real time and offline analysis by non-data scientists. If you’re getting started with Hadoop this talk is just for you.

Karthik RamasamyStaff Data ScientistLinkedIn

Greg DePalma is Vice President of Audience Insights at TiVo Inc., where he consults with advertiser, agency, and network clients to increase commercial effectiveness in a DVR world. Previously, Greg worked as Senior Director, Brand Marketing at LendingTree, where he managed the brand, advertising, sports marketing and media. During his 18-year marketing and advertising career, Greg has worked at industry leaders like WPP's Millward Brown and Nielsen Media Research.

Eric DalyVP, Global Reporting & AnalyticsSony Pictures Entertainment

Meeting Demand for Movies & TV Shows in Retail

Entertainment continues to be one of America’s biggest exports.   But how do you forecast and meet demand for our product here in the United States?   This presentation will look at some of the variables and techniques used in forecasting demand for movie and television shows as early as the greenlight process (the decision to make a movie or TV show in the first place) to the time period just before the product is released on home video. We also look at ascertaining demand among retailers based on the title being sold.

Confirmed Speakers

Megan Huth is a People Scientist at Google in Mountain View, CA.   She works in People Analytics, a group devoted to using social science to better understand how to make Google a great place to work.  Within People Analytics, she is part of the People and Innovation Lab (PiLab), an internal HR think-tank focused on pushing the boundaries of organizational science.  PiLab research has been featured in the   New York Times, HBR, HR Executive Online, among others. She has experience with survey design, performance management, and well-being at work. She holds a PhD from Michigan State University in Organizational Psychology.

Megan HuthPeople ScientistGoogle

Applying Advanced Analytics to HR

Google believes that all people decisions should be supported by science and data. In the pursuit of this goal, the People Analytics team at Google uses scientific methodologies to better understand individuals’ complex work-lives. In this presentation, we will review some current initiatives underway at Google. These include s discussion of collecting and using longitudinal data, appropriately applying data imputation to large, messy data sets and thoughtful use of machine learning text analysis. The session will conclude with a discussion of ethical considerations important when applying advanced analytics to HR.

Mario Vinasco Director, Analytics & Data ScienceFacebook

Mario Vinasco has over 18 years of progressive experience in data driven analytics with emphasis in database programming and predictive models creatively applied to eCommerce, advertising, customer acquisition/retention and marketing investment. Mario specializes in developing and applying leading edge business analytics to complex business problemsMario holds a Masters in Engineering economics from Stanford University and currently works for facebook as data scientist; In this role he has been providing optimization recommendations to internal search and other critical IT operations.Prior roles included VP of business intelligence in digital textbook startup, people analytics manager at Google and eCommerce Sr manager at Symantec.

Predictive Analytics & Business Insights: Practical Uses in eCommerce & Marketing

A/B testing is the best way to optimize the customer experience, select acquisition channels and allocate investments ; however , customer segmentat ion , identification of risk and potential and close monitoring of testing performance are essential components of the strategy. Predictive models can be of great help, as these can identify likely customer shopping behaviors, or they can rank channels based on several factors. These can then be run through tests to determine winning customer experiences. Predictive models can be simple and easy to implement, as in macro investment allocation; they can also be elaborated as in deeper customer segmentation.

Hobson and his data analyt ics teammates are transforming the way business decisions are made at SHARP, using data to reveal new opportunities and revamp existing business strategies. Hobson brings 20 years of innovation and data analytics experience in a variety of roles and industries:   Section Head at Northrop Grumman, Quant for a Point Clear Capital, Visualization Developer at Squishy Media, Chief Data Scientist at Building Energy, and now Principal Data Scientist at Sharp Labs.

Hobson LanePrincipal Data ScientistSHARP Laboratories of America

Predictive Analytics War Stories

Imagine yourself in the operations center for a $1B satellite trying to make sense of data streaming back from its sensors as it accelerates out of control. Or imagine watching your service center expenses accelerating until they exceed $3M/month. This talk will relate these and other "million dollar" war stories where decision-makers learned the hard way that having data analytics experts on your team is not enough. 

Confirmed Speakers

Jack Y. Chen is a Chief Data Scientist/Marketing Decision Science Director at Dell specializing in Investment Optimization, Customer Targeting, and CRM related advanced analytics. He works in measuring long-term impacts of difficult to measure influences such as brand campaigns, social media, corporate social responsibility and total quality management improvements. He is lead inventor on two patented modeling techniques including an overall investment model, a brand health model, and social media targeting.   In previous roles, he has worked in Risk Management on both front end origination and back end portfolio management across consumer, SMB and enterprise.  He received his PhD degree in statistics and his MBA in finance from Iowa State University. 

Jack ChenChief Data ScientistDell

Revolutionizing Decision Making: How Analytics Will Take Over the Business

With advances in big data, artificial intelligence and increased metric captures of everything we do, analytics will go through a radical transformation in the next few decades. As a result, there will be a shift from analytics simply influencing business decision makers to analytics actually owning the decisions. This transformation is already happening in the pricing community, but expect it to expand to even CFO-level decisions. 

Fabian Alenius Product Owner, Analytical ComputationSpotify

Spotify brings you the right music for every moment. WIth over 24 million users and 20 million songs, Spotify has to deal with vast amounts of   data   everyday. Over the last few years Spotify has seen a small hadoop cluster for reporting grow into a platform that feeds the entire organization with   data.   Fabian Alenius is a Product Area Lead for Data   Infrastructure at Spotify and has seen the transition firsthand.

Data Infrastructure & Analytics at Spotify

This presentation will give an overview of Spotify's data infrastructure and explain our architectural and organizational transformation by looking at it with a historical context. We will share some of the analytics we do by zooming in on a few key use-cases and looking at what infrastructure is required. We will also share some of the problems we have faced over the last few years and a few of the lessons learned.

Ky Harlin is Director of Data Science at BuzzFeed. With over eight years of experience in data-driven research, mining, and software development, his primary research interests include the design and analysis of viral marketing and advertising campaigns across social networks.   Ky developed a statistical methodology for detecting viral publisher content (patent pending), for which he was named one of "21 New Media Innovators" by New York Magazine.   He was also named "BuzzFeed's Secret Weapon" by the American Journalism Review for his work employing data-driven methodologies at the company. Prior to joining BuzzFeed, Ky worked in medical research, developing mathematical analysis methods and software tools for nuclear imaging. 

Ky HarlinDirector, Data ScienceBuzzFeed

Using Data Science to Crack the Social Code

Join Ky Harlin, BuzzFeed's Director of Data Science to learn how BuzzFeed uses statistical methodologies to predict social content and how to integrate strategic data-driven research, mining and software development to grow audience online. 

Confirmed Speakers

Alex Garcia is certified Master Black Belt leading the Test & Learn Team within Global People Analytics Organization since January 2014. The team is responsible to generate concepts from insights and lead measurement of any major global initiative that impacts our associates. Prior to this role, he led the Global Continuous Improvement Team at Walmart for 7 years. Alex background is bachelor’s in Mechanical/Electrical Engineering from ITESM (Mexico), MS in Mechanical Engineering from UIUC and MBA from J BU. Previous to joining Walmart, Alex had 10 years of manufacturing and process improvement experience from Nemak, General Motors and United Technologies.

Alex Garcia Director, Test & Global People AnalyticsWalmart

Analytics Approach to Business Transformation

In the past, the approach to Business Transformation often leads companies to sub-optimization and eventually re-deployment of resources to new initiatives to solve the same business challenge. A more rigorous Analytical approach can lead to development and validation of concepts that with a strong focus on Execution and Change Management can lead to long term solution of Business Challenges through Continuous Improvement.

Mohitdeep Singh Data ScientistRdio

Mohit is a data scientist on Rdio's data science team since 2014, working on both research and implementing recommendations, playlisting and similarity problems. His research interests includes numerical linear algebra, graph-based machine learning, randomized linear algebra and variational inference on statistical models. He was also a contributor to graphlab v1.0. He is also collaborating on a research with folks at Lawerence Berkeley National Lab where he is implementing a randomized linear algebra library on spark.

Music. Tuned to you

Rdio is an online music service that offers music streaming services in 60 countries. In this talk, we will discuss some of the large-scale machine learning problems Rdio's data science team is addressing: Artist Similarity & playlisting. So far we have focused on collaborative approaches. We will compare different techniques and evaluate them across rdio dataset. We will also share some of the challenges we face and future data products in pipeline.

Sastry is Chief Architect at StubHub, responsible for the overall technology architecture, strategy and direction. This includes both platform and application architecture, serv ice or ientat ion , domain model ing , content management, information discovery, big data platform and enterprise architecture. Sastry works with and leads a team of architects and closely collaborates with product management, engineering and business leads.  Sastry is a veteran technologist with nearly two and half decades of experience developing, leading and architecting various highly scalable and distributed systems,  

Sastry MalladiChief ArchitectStubHub

Big Data Platform at the Worlds's Largest Fan-to-Fan Ticket Marketplace

StubHub is the world's largest secondary online ticket marketplace serving millions of users and is on course to transforming itself into the source fans rely on to discover, access and share entertainment experiences worldwide.   In order to achieve that, we need a comprehensive big data platform to handle a variety of data sources, data types and use cases, including, but not limited to, personalized recommendations and   analytics. We use a hybrid data platform that employs a traditional data warehouse as well as a Hadoop based platform. This session will describe our use cases, challenges we face and the approach that we took to address these.

The Information

Silver Pass

$1595Access to all sessions &

networking events7 days access to presentations from the

summit via ieOnDemand

$1395Early Bird Price(before Dec 12)

Diamond Pass

$2095Access to all sessions, networking

events, annual subscription to all content on the Big Data & Analytics channels via

ieOnDemand

$1895Early Bird Price(before Dec 12)

Gold Pass

$1895Access to all sessions, networking

events & unlimited access to presentations from the summit via

ieOnDemand

$1695Early Bird Price(before Dec 12)

Registration Pricing

7

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Ways to Register+1 415 315 9533 +1 323 446 7673 Register Online Here

1 Day Pass

$795Full access to the sessions to your chosen day of the summit, 7 days

access to presentations from the summit via ieOnDemand

$695Early Bird Price(before Dec 12)

On-Demand Pass

$600Unlimited access to presentations from the summit via ieOnDemand,

including presentations, interviews & the ability to contact speakers

Unlimited access to summit presentations

via ieOnDemand

Predictive Analytics Innovation SummitDate: February 12 & 13, 2015City: San Diego, CA Venue: The Westin San DiegoReservations: IE. has secured a discounted room rate at the Westin San Diego for the nights of the conference. Secure your room here

For larger groups or special requests contact Andrew by calling +1 415 315 9533 or email achristofi@theiegroup.com* Team discounts are applicable at the point of registration only.

Group Discount Offers3 Silver Passes: $3300 ($1100 per attendee)5 Silver Passes: $4750 ($950 per attendee)3 Gold Passes: $4200 ($1400 per attendee)5 Gold Passes: $6250 (£$250 per attendee)3 Diamond Passes: $4800 ($1600 per attendee)5 Diamond Passes: $7250 ($1450 per attendee)

Access All Areas

$2295Diamond Pass with additional access to the co-located Data Science Innovation and

Apache Hadoop Innovation Summits

$2095Early Bird Price(before Dec 12)

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1. Delegate Information

2. Pass TypesEarly Bird Pass Options until December 12, 2014

Early Bird Silver: $1395 Attendees ____ Early Bird Gold: $1695 Attendees ____ Early Bird Diamond: $1895 Attendees ____

Regular Pass Options after December 12, 2014 Silver Pass: $1595 Attendees ____ Gold Pass: $1895 Attendees ____ Diamond Pass: $2095 Attendees ____

Group Discount Pass Options 3 Silver Passes $3300 ($1100 per attendee) 5 Silver Passes $4750 ($950per attendee) 3 Gold Passes $4200 ($1400 per attendee) 5 Gold Passes $6250 ($1250 per attendee) 3 Diamond Passes $4800 ($1600 per attendee) 5 Diamond Passes $7250 ($1450 per attendee)

For larger groups or special requests contact Andrew by calling +1 415 315 9533 or email achristofi@theiegroup.com* Team discounts are applicable at the point of registration only.

Pass Descriptions:Silver Pass: Access to all sessions & networking eventsGold Pass: Access to all sessions, networking events & unlimited access to ieOnDemandDiamond Pass: Access to all sessions, networking events, annual subscription to all content on the Big Data & Analytics channels via ieOnDemand

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Prices are exclusive of VAT. Places are transferable without any charge to another Summit occurring within 12 months of the original purchase. Team discounts are applicable at the point of registration only. Any cancellations within a group registration will in turn incur an increase in registration fee for the remaining group participants. Cancellations before January 12, 2015 incur an administrative charge of 50%. If you cancel your registration after January 12 2015 you will be charged the full fee. You must notify The Innovation Enterprise in writing of a cancellation, or you will be charged the full fee. The Innovation Enterprise reserve the right to make changes to the program without notice. NB: FULL PAYMENT MUST BE RECEIVED BEFORE THE EVENT.

Registration FormPredictive Analytics Innovation SummitFebruary 12 & 13, 2015 | The Westin | San DiegoFor registration or more information on the program, please call Andrew on +1 (415) 315 9533, or fax this registration form to +1 (323) 446 7673

3. Payment Options

Schedule

Networking Drinks 17.00 - 19.00

February 13

Session One 08.30 - 10.00

Coffee Break 10.00 - 10.30

Session Two 10.30 - 12.00

Lunch 12.00 - 13.30

Session Three 13.30 - 15.00

Coffee Break 15.00 - 15.30

Session Four 15.30 - 17.00

Day Two

February 12 Day One 08.30

10.00

10.30

12.00

13.30

15.00

15.30

17.00

19.00

08.30

10.00

10.30

12.00

13.30

15.00

15.30

17.00

Session Five 08.30 - 10.00

Coffee Break 10.00 - 10.30

Session Six 10.30 - 12.00

Lunch 12.00 - 13.30

Session Seven 13.30 - 15.00

Coffee Break 15.00 - 15.30

Session Eight 15.30 - 17.00

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Sponsors

For sponsorship information contact Euan at ehunter@theiegroup.com F TI L

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