October 24-27, 2016
New York
Delivering on the promise of data science
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Speakers

 Dean Abbott

Dean Abbott

Co-Founder and Chief Data Scientist

SmarterHQ

@deanabb

Dean Abbott is Co-Founder and Chief Data Scientist of SmarterHQ, and President of Abbott Analytics, Inc. in San Diego, California. Mr. Abbott is an internationally recognized data mining and predictive analytics expert with over two decades of experience applying advanced data mining algorithms, data preparation techniques, and data visualization methods to real-world problems, including fraud detection, risk modeling, text mining, personality assessment, response modeling, survey analysis, planned giving, and predictive toxicology.


Mr. Abbott is the author of Applied Predictive Analytics (Wiley, 2014) and co-author of IBM SPSS Modeler Cookbook (Packt Publishing, 2013). He is a highly-regarded and popular speaker at Predictive Analytics and Data Mining conferences and meetups, and is on the Advisory Boards for the UC/Irvine Predictive Analytics Certificate as well as the UCSD Data Mining Certificate programs.


He has a B.S. in Mathematics of Computation from Rensselaer (1985) and a Master of Applied Mathematics from the University of Virginia (1987).

Keynote: The Revolution in Retail Customer Intelligence

 Kumar Amitesh

Kumar Amitesh

VP & Head

TCS BPS, North America

Kumar Amitesh heads Business Process Services for North America at Tata Consultancy Services (TCS) Amitesh has rich experience in Business & Technology Operations, Process & Consulting. In his previous role, he headed Global BPS Solutions & Offerings for TCS BPS and was instrumental in growing the TCS BPS brand. He is credited with ensuring a differentiated positioning for TCS BPS through an industry focused solutions and offerings structure which contributed to TCS driving a domain based BPS services. He has been an evangelist throughout his career and is credited with many firsts for the organizations he has worked for. His eye for detail and spotting markets trends and opportunities has helped him create solution and offerings for TCS where none existed. He has been an active speaker in various forums representing the organisations he worked for on Supply Chain, Procurement and BPS services.

With 20 years in the industry, Amitesh has handled leadership positions as a Business Head and Growth Head for industry verticals like Energy-Utility, Travel-Transportation-Hospitality, Healthcare and Media-Entertainment. He has also worked extensively in the Procurement /Supply Chain space and in Asia Pacific Markets like Singapore, China and Australia/NZ. Amitesh has also played crucial roles in the inorganic growth opportunities and brings in the experience of various M&A initiatives he has been part of.

Gold Sponsor Presentation:Predictive Analytics in the Digital Era

 Charles Berger

Charles Berger

Sr. Director, Product Management, Data Mining and Advanced Analytics

Oracle

Charlie Berger is Sr. Director of Product Management, for Data Mining and Advanced Analytics at Oracle. He has over 30 years of experience in data analysis software including Oracle, Thinking Machines Corporation, Bolt, Beranek and Newman, Palladian (expert systems), Automatix (robotics and machine vision), Honeywell Computers and IBM. He is responsible for product management and direction of Oracle's in-databases' data mining and predictive analytics technology including data mining, text mining and SQL based statistical functions. He holds a MS in Manufacturing Engineering and an MBA both from Boston University. He holds a BS in Industrial Engineering and Operations Research from the University of Massachusetts at Amherst.

Diamond Sponsor Presentation: Big Data Analytics using Oracle Advanced Analytics12c and Big Data SQL

 Michael Berry

Michael Berry

Analytics Director

Tripadvisor Hotel Solutions

Michael Berry is co-author of some of the most widely read and respected books on data mining including Data Mining Techniques for Marketing, Sales, and Customer Relationship Management which is now in its third edition. These best sellers in the field have been translated into many languages. Michael is an active practitioner of data mining. His books reflect many years of practical, hands-on experience down in the data mines. Michael is Director of Analytics at Tripadvisor for Business, the B2B side of Tripadvisor, the world’s largest travel-related web site. Prior to joining Tripadvisor, he spent many years as a data mining consultant and educator.

Session: Picking the Right Modeling Technique for the problem

 Dave  Bose

Dave Bose

V.P., Modeling and Simulation

Analytical Mechanics Associates, Inc.

Dave is an aerospace engineer helping businesses predict and manage their future through analytics, modeling and optimization. He is Vice President of Modeling and Simulation at Analytical Mechanical Associates, Inc. He focuses on advanced business analytics. He guides and contributes to technology development in the business analytics space and its application to problems in industry, particularly financial services and education. Before this he worked at Boeing where he developed analytical models of flight systems and subsystems. He also performed simulation analysis to predict system performance and design control systems for system automation and to assess system stability.

Session: What Landing a Rover on Mars Taught us about Optimization of Marketing Strategies for Loan Portfolios

 Werner Britz

Werner Britz

Head of Decision Science

RCS Group

Werner Britz has spent the past five years in the Consumer Credit Risk industry, including the last two at RCS Group which focuses on Retail Credit. In his role at RCS Group, Werner is heading up the Decision Science department who is responsible for predictive analytics, forecasting, optimization and R&D through the entire credit life cycle and business operation. His team has an in-depth understanding of Credit Risk assessment through credit scoring, developing credit scorecards, dual score matrix designs, financial forecast model and provision models. Werner has a passion for mining data to predict behaviour and outcomes.

Session: Recoveries: External Debt Collection Optimization

 Rick Chin

Rick Chin

Director of Product Innovation

SolidWorks

Rick Chin has 30 years of experience in the Computer Aided Design (CAD) field. In his current role, he is tasked with coming up with new software products. This is accomplished through customer research, product conceptualization, prototyping, and the shepherding of new product launches. Past SolidWorks accomplishments include eDrawings, FeatureXpert, Sustainability, and Augmented Reality in eDrawings. In 2000 he had also founded his own company, Xpress3D, an online 3D Printing company.

His work is directed by "Emotionally Driven Product Innovation", which focuses innovation on people first, then turns to technology second. This is why projects like "market segmentation described with personas" and this "user segmentation based on product use" were pursued. He believes that customer segmentations such as these provide actionable knowledge about customers.

Session: Driving Product Improvements and Marketing Efforts through Software Usage Logs

 Lawrence Cowan

Lawrence Cowan

Senior Partner & COO

Cicero Group

Lawrence is a Partner at the Cicero Group, a leading data-driven strategy consulting firm located in Salt Lake City, UT. Lawrence has spent the last eight years building Cicero's analytics practice where he has experience helping Fortune 500 firms solve real business challenges with data, including attrition, segmentation, sales prioritization, pricing, and customer satisfaction. Lawrence is also an expert in choice modeling (choice-and menu-based conjoint), having successfully deployed and implemented more than 50 studies in his career at Cicero, relying upon Hierarchical Bayesian and Latent Class analysis to derive accurate market based scenarios. Lawrence holds a Master's of Science in Predictive Analytics from Northwestern University, an MBA with an emphasis in Business Economics from Westminster College, and a BA from Brigham Young University.

Session: Pricing and Segmentation Utilizing Menu-based Conjoint

 Dave Dimas

Dave Dimas

Lecturer, Department of Mechanical and Aerospace Engineering Director, Engineering, Sciences and Information Technology Programs - Extension

University of California, Irvine

Dr. Dimas is a lecturer in the Department of Mechanical and Aerospace Engineering and the Director of Information Technology, Engineering and Science programs for the University of California, Irvine. In this latter role he is tasked to insure that the US workforce has the skills required to meet the changing needs of the business community. He has developed many certificate programs including Predictive Analytics, Data Science, Big Data, Data Management, Web Intelligence and Business Intelligence and Data Warehousing. Dr. Dimas has been a lecturer for the school of engineering for over 20 years. His teaching and research areas include; numerical analysis, engineering simulation, product lifecycle management and effective educational methods in STEM.

Dr. Dimas also worked at Santa Ana, Calif.-based MSC Software corporation for over 25 years. While at the simulation solutions company, he served in a number of top-level management positions including director of customer support, training services, educational sales and product documentation. In this role he implemented several analytics-based systems and processes that included a global CRM system that significantly improved the operational efficiency of the organization. In addition, he worked for Costa Mesa-based PDA Engineering as director of support and training deploying similar tools and processes to efficiently run the business while keeping customer satisfaction levels high.

Dimas received his bachelor's degree in mechanical engineering from UC Irvine in 1978, master's degree in engineering mechanics in 1979, and a Ph.D. in civil engineering in 1988. Since 1985, Dimas has played an active role in the university's Henry Samueli School of Engineering securing several large donations to the School, valued cumulatively at more than $20 million. He was also honored with the university's distinguished alumni award in 2006.

Expert Panel: Education and Training Options for Predictive Analytics

Dr. John Elder, Ph.D.

Dr. John Elder, Ph.D.

Founder & Chair

Elder Research

@johnelder4

John Elder chairs America's most experienced Data Science consultancy. Founded in 1995, Elder Research has offices in Virginia, Maryland, North Carolina and Washington DC. Dr. Elder co-authored 3 award-winning books on analytics, was a discoverer of ensemble methods, chairs international conferences, and is a popular keynote speaker. John is occasionally an Adjunct Professor of Systems Engineering at the University of Virginia, and was named by President Bush to serve 5 years on a panel to guide technology for national security.

Special Plenary Session: Top Five Technical Tricks to Try when Trapped

 Will Ford

Will Ford

Director of Data Science

Predixion Software

Dr. Will Ford is the Head of Expert Services/Data Science at Predixion Software. Dr. Ford’s team of data scientists help Predixion’s customers realize the value of predictive analytics. Dr. Will Ford started his career in distributed computation and analysis more than a decade ago at the Pittsburgh Supercomputing Center(PSC). Following his work at the PSC, Dr. Ford spent several years at Caltech studying applied statistical modeling and optimization for problems in biochemistry and chemistry. Dr. Ford has held several consulting roles and during that time has helped to build two data science teams. Dr. Ford has co-published a variety of scientific articles and is a frequent speaker on data science and consulting related topics.

Expert Panel: Education and Training Options for Predictive Analytics

 Mohamed Guidoum

Mohamed Guidoum

Chief Strategy Officer

AIMS

Dr Guidoum holds a BSc, MSc and PhD in Chemical Engineering from British universities. He taught at the Universitie de Constantine in Algeria for few years before moving to Abu Dhabi. He joined an Adnoc affiliate where he held the responsibilities of corporate services director for over a decade.
During his tenure, Dr. Guidoum and his team used SAS to model data and achieve a 35% reduction in manpower for a 3,000+ employees unit and other major business improvements like forecasting and logistics optimization.

At ADWEA, Dr. Guidoum led the ASTRO (ADWEA Strategic Transformation) at ADWEA where he was responsible for corporate strategy and performance management. He is currently the Chief Strategy Officer at AIMS and his work focuses on big data and analytics to drive strategy execution. He is a certified Kaplan-Norton Execution Premium Process Practitioner and considered a renowned expert on the balanced scorecard in the GCC region.

Session: Driving Strategy Execution Using Big Data Analytics

 Thomas Hill, Ph.D.

Thomas Hill, Ph.D.

Executive Director Analytics

Dell Software Group

Dr. Thomas Hill is Executive Director for Analytics at Dell Software Group. He joined Dell through the acquisition of StatSoft Inc. in April 2014, where he had been Senior Vice President for Analytic Solutions for over 20 years and was responsible for building out Statistica into a leading analytics platform. Dr. Hill received his Vordiplom in psychology from Kiel University in Germany and earned an M.S. in industrial psychology and a Ph.D. in psychology and quantitative methods from the University of Kansas. He was on the faculty of the University of Tulsa from 1984 to 2009, where he conducted research in cognitive science and taught data analysis and data mining courses. He has received numerous academic grants and awards from the US National Science Foundation, the National Institute of Health, the Center for Innovation Management, and other institutions. Over the past 20 years, his team has completed diverse consulting projects with companies from practically all industries and has worked with leading financial services, insurance, retailing, manufacturing, pharmaceutical, healthcare, and other companies in the United States and internationally on identifying and refining effective predictive modeling solutions for a broad scope of applications. Dr. Hill has published widely on innovative applications for data mining and predictive analytics and is also the author (with Paul Lewicki, 2005) of "Statistics: Methods and Applications," the "Electronic Statistics Textbook" (a popular on-line resource on statistics and data mining), and a co-author of "Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications" (2012) and "Practical Predictive Analytics and Decisioning Systems for Medicine" (Elsevier/Academic Press, 2014). Hill is also a contributing author to the popular "Handbook of Statistical Analysis and Data Mining Applications (2009)."

Expert Panel: Education and Training Options for Predictive Analytics

 Mahesh Jagannath

Mahesh Jagannath

Senior Manager, Business Intelligence

Dunkin Brands

Mahesh Jagannath has over 20 years of experience in software product development and services industry with a focus on Business Intelligence and Database Systems software. He has an excellent understanding of Business Intelligence and Database Systems technologies and markets (Oracle RDBMS in particular). He has consistently and successfully led and managed several cross-functional teams of architects, engineers and functional analysts working closely with clients to ensure business success. At Dunkin' Brands, Mahesh owns the development and delivery of all Business Intelligence solutions including Advanced Analytics / Data Science. Mahesh holds a Master's in Computer Science from University of Florida and an M.B.A. from Babson College, Wellesley. Mahesh has authored several papers, presentations and patents over the years in areas related to Databases and Analytics.

Diamond Sponsor Presentation: Dunkin Brands Turn Big Data into Big Advantage Case Study

 Herman Jopia

Herman Jopia

First Vice President and Data Analytics Manager

American Savings Bank

Herman Jopia is First Vice President and Data Analytics Manager at American Savings Bank. Industrial engineer with a master’s degree in statistics and an MBA, Herman has ten years of experience in retail banking in Chile and US, leading the analytic units of credit risk and marketing, managing several data driven projects such as credit scoring, response and attrition models, loss forecasting, and price optimization; monitoring key performance metrics of the portfolio, handling credit bureaus and analytic vendors, and reporting on a regular basis to top management and regulators.

Herman is also author of the R package "Optimal Binning for Scoring Modeling", an open source code that reduces the time consuming process of generating predictive characteristics for modeling.

Herman also develops talent through the Analytics Internship at ASB for top students in Hawaii and leads the Honolulu R Users Group, which he founded early in 2015.

Session: Driving Superior Growth Through Self-Developed Code, Scoring Modeling, and Price Optimization

 Bruce Lacey

Bruce Lacey

Vice President of Engineering

Carrier iQ

Bruce brings years of industry-leading management and technical expertise within mobile telecoms to Carrier iQ. As the founding Vice President of Engineering and Technology for Carrier iQ, Bruce led the development and deployment of CiQ’s Mobile Analytics technologies comprising a zero-footprint intelligent agent, an extensible big data analytics platform, and advanced statistical inference analytics that address real market problems. Prior to CiQ, Bruce led large scale advanced technology initiatives for emerging growth companies and the defense industry. Bruce earned a Bachelor’s degree in computer science and mathematics from the University of Massachusetts at Amherst.

Session: Unleashing Smartphones for Exabyte-Scale Analytics

 Scott Lancaster

Scott Lancaster

Vice President

State Street Corp.

Scott Lancaster, a VP at State Street, is part of the Application Development & Maintenance Governance in their IT organization and leads Performance Analytics and Estimation Center of Excellence along with other program management responsibilities.

Prior to his current role he worked in the Basel II PMO using analytics to manage the critical path. Before working for State Street, Scott worked for IBM/Rational as project manager, software services consultant, and technical field sales specialist where he assisted Fortune 500 clients in deploying improved software development and business processes.

Scott began his interest in predictive analytics and estimation over 20 years ago while working for Intel. He has a Bachelor of Science in Computer Science and expects to receive his Master of Science in Predictive Analytics from Northwestern in 2015. He has over 24 years of experience in the technology industry and is a certified Project Management Professional (PMP).

Session: Predictive Analytics for Project Management--Cost Avoidance

 Victor Lo

Victor Lo

Vice President

Fidelity Investments; Bentley University

Victor S. Y. Lo is a Vice President at Fidelity Investments and visiting research fellow/executive-in-residence at Bentley University. Previously, he was VP and manager of modeling and analysis at FleetBoston Financial, and senior associate at Mercer Management Consulting (now Oliver Wyman).

He has over 20 years of experience in analyzing real life data, applying quantitative methods to numerous business areas such as customer relationship management, advertising strategy, market research, database marketing, financial econometrics, risk management, transportation, insurance, and human resources.

Additionally, Victor has been actively engaged with Big Data analytics, practical causal inference, and is a pioneer of Uplift/True-lift modeling. Victor has managed teams of quantitative analysts in multiple organizations.

Victor earned a master degree in operational research and a doctorate in statistics, and was a postdoctoral fellow in management science. He has co-authored a graduate level econometrics book and published articles in data mining, statistics, and management science.

Session: Uplift Modeling and Uplift Prescriptive Analytics for Multiple Treatments

 David McMichael

David McMichael

Second Vice President

Travelers

David McMichael is responsbile for oversight of Research & Modeling within the Commercial Actuarial Strategic Development (CASD) team at Travelers. CASD is dedicated to advanced predictive modeling for Business Insurance at Travelers.

Prior to joining Travelers, David worked for MetLife, Allstate, and the Florida State University Mathematics Department. David holds a bachelors degree from the University of Kentucky, and masters and doctoral degrees from the University of Wisconsin, all in Mathematics. David is a Fellow of the Casualty Actuarial Society.

Session: A Journey along the Predictive Analytics Maturity Curve

 Sears Merritt

Sears Merritt

Vice President, Chief Data Scientist

MassMutual Financial Group

As Chief Data Scientist, Sears Merritt leads the Data Science Program (http://datascience.massmutual.com) at MassMutual Financial Group. In various roles, including founder, engineer, researcher,and technology advisor, he has spent over 10 years working with data and big data systems in industry and academia. Sears holds a Ph.D. in Computer Science, an M.S. in Telecommunications and a B.S. in Electrical Engineering all from the University of Colorado at Boulder. He has also earned expert level IT certications in networking (CCIE, routing and switching), project management (PMP), and security (CISSP).

Session: Predictive Analytics in Life Insurance

 Paul Mlakar

Paul Mlakar

Co-Founder and Managing Partner

R2M Solution

Mr. Mlakar is Co-Founder and Managing Partner of R2M Solution with a unique career as a former military officer, a Fortune 100 Division Vice President, and CEO of BiologicsMD. Mr. Mlakar has a B.S. Civil Engineering degree from the United States Military Academy and a M.B.A. from the University of Arkansas.

Session: "Confucius says..." - Using Analytics to Predict Construction Bids

 Bin Mu

Bin Mu

VP, Business Analytics

MetLife

Bin Mu is the Vice President, Data Science of MetLife. In this capacity, he is responsible for applying advanced analytics to identify and explore business opportunities, increase topline sales, and improve operation efficiency and effectiveness. He currently leads a team of 20 data scientists that supports MetLife’s business across all the product lines. Before joining MetLife, Bin was the Global Head of Data Analytics at Cigna, responsible for all the analytics to support group business. Prior to that, Bin Mu held various analytics leadership positions at Deloitte, Limited Brands, and The Hackett Group.

Bin Mu is a competitive marathoner and active triathlete.

Session: Establishing Value: the "Making Impact Through Analytics" Framework

 Philip O'Brien

Philip O'Brien

MIS and Portfolio Manager

Paychex

Philip O'Brien is responsible for the predictive analytics program at Paychex Inc., a leading provider of payroll, human resource, insurance, and benefits outsourcing solutions for small- to medium-sized businesses. The predictive analytics team at Paychex has implemented models to help with strategic decisions across all aspects of the business, including effectively targeting retention strategies, assisting in dynamic cross-sell initiatives, improving collection targets for bottom line results, and driving client service progression strategies.

Philip has been with Paychex for 15 years and has served in a leadership capacity within analytics for the past ten years. For well over a decade, Paychex has developed its predictive analytics program and has earned industry recognition for its leadership in the space. The predictive analytics function at Paychex continues to grow and add value across the organization, with more than 20 models divided between four portfolios: Operations, Sales, Risk, and Strategy.

Session: Predicting Employee Churn with Anonymity

 Justin Petty

Justin Petty

Vice President, Client Solutions Media and Partnerships

84.51°

As Vice President, Media Solutions and Partnerships, Justin Petty cultivates and designs partnerships with media companies that allow clients to target and measure digital media programs utilizing household level shopping behavior. Responsible for developing 84.51°'s media solutions portfolio, he enables retailers and brands to relevantly engage their customers outside of the physical store. Petty oversees the development of joint solutions with external partners that leverage customer-centric targeting and measurement for television, digital, social and other media. Additionally, he oversees the technical and analytical teams creating new products and services in the media space.

Prior to 84.51°, Petty served in a media solutions role for dunnhumby assisting retailers and consumer packaged goods brands with marketing strategy, execution and planning. Working with some of the largest retailers and brands in the world, he executed and optimized media programs for them to reach their customers in a more relevant and personalized manner. Petty successfully built dunnhumby's media solutions business from start-up phase, to over $7 million annually in the U.S. and +$10 million globally.

Prior to dunnhumby, Petty served as Senior Director of Analytics at Aspen Marketing Services, where he provided integrated analysis for clients in the telecommunications and automotive industries. He held similar responsibilities at SRI Analytics, which was acquired by Aspen Marketing Services during his tenure. Petty began his career as an Analyst at Equifax, where he built predictive models for credit risk behavior.

Petty holds a Master of Science in Statistics from the University of Kentucky and a Bachelor of Science in Mathematics and Geography from Samford University.

Session: Cross-Platform Media: How to Leverage Household Response Modeling and Track Campaign Measurement

 Dan Potter

Dan Potter

Chief Marketing Officer

Datawatch Corporation

Dan Potter is Chief Marketing Officer at Datawatch Corporation. In this role, Dan is responsible for the worldwide marketing communications, product marketing and go-to-market strategies for Datawatch. Prior to Datawatch, Dan led the product marketing and go-to-market strategy for IBM's personal and workgroup analytics products and the online community and social media strategy for IBM's AnalyticsZone.com initiative. Prior to IBM, he held senior roles at Oracle, Progress, and Attunity where he was responsible for identifying and launching solutions across a variety of emerging markets including cloud computing, real-time data streaming, federated data, and e-commerce.

Dan is an accomplished public speaker with numerous presentations delivered at major events including Java One (2001), CES (1999), Oracle OpenWorld (1999), IBM Information on Demand (2010-2015), and the CEO Summit. He has been recognized by Mass High Tech as "Mover & Innovator" (May 2005) and a recipient of Oracle President's Award for Outstanding Contribution.

Diamond Sponsor Presentation: New Advances in Data Preparation for Advanced Analytics

Dr. Satyam Priyadarshy

Dr. Satyam Priyadarshy

Chief Data Scientist

Halliburton

Dr. Satyam Priyadarshy is a pioneer in the fields of data science, big data, analytics, and emerging technologies. He is currently chief data scientist at Halliburton's Landmark PSL, leading expansion of integrated workflow capabilities and other data development initiatives.

Dr. Priyadarshy has appeared as speaker at several international conferences, and has written, co-authored, presented and published numerous research papers in peer-reviewed journals and magazines. He has held various leadership positions in AOL, Network Solutions, Acxiom Corporation prior to joining Halliburton. He was recently named to The Financial Times' list of potential board candidates with emerging technology and analytics expertise. Dr. Priyadarshy is an adjunct faculty at Georgetown University. He is currently senior fellow at the International Cyber Security Center at George Mason University. He is advisory board member at multiple organizations including Big Data Summit, Virginia Tech's MBA Board, etc. Dr. Priyadarshy holds a Ph.D. from Indian Institute of Technology in Bombay, and an MBA from Virginia Tech.

Session: Challenges in Leveraging Predictive Analytics for Big Data in Oil and Gas

 Boris Rabinovich

Boris Rabinovich

Lead Data Scientis

Perion Networks

Boris Rabinovich is a lead Data Scientist at Perion networks. His experiences range from hands-on implementation of predictive modeling for real-time-bidding systems and constrained optimization to statistical process control and AB testing. His work involves end-to-end development of machine learning algorithms in a challenging big data environment. He graduated from Ben-Gurion University with an M.Sc. in Information Systems Engineering. His thesis project involved designing and developing a schema matching algorithm.

Session: Early Detection of Long Term Evaluation Criteria in Online Controlled Experiments

 Madhusudan Raman

Madhusudan Raman

Innovation Incubator

Verizon

Madhu Raman is a practitioner who incubates beachhead market ideas that 'touch' the connected consumer. An alum of the MIT Sloan Executive Strategy & Innovation Program and an Electrical Engineer, Madhu heads Verizon's global ideation incubation services practice based out of their Massachusetts Innovation Center. His innovations include numerous granted or in-process patents leveraging Big Data contextual insight harnessing predictive models, the cloud, consumer social media, and mobility.

Madhu's experience includes establishing a successful Fortune 500 Prototyping Practice for a major startup in the 90's and since 98' co-founding, working in, and with startups as a c-level thought leader and technology board advisor. Ideation pipeline governance, systematic innovation discovery, agile market testing and product tuning leveraging native, open sourced and, acquired intellectual property continue to be a key part of Madhu's current role. He enjoys volunteering in local homeless shelters alongside his family.

Session: Predicting Behaviorial Influence in Real-Time for Dynamic Offers

 Steven Ramirez

Steven Ramirez

CEO

Beyond the Arc

@beyondthearc

Steven J. Ramirez is the chief executive officer of Berkeley, Calif.-based Beyond the Arc, Inc., a firm recognized as a leader in helping companies transform their customer experiences by leveraging advanced analytics.

In addition to developing and executing the vision for Beyond the Arc, Ramirez leads teams of data and strategy consultants committed to client success. They analyze customer and social media data, combined with text analysis, to drive customer growth, improve customer retention, understand service breaks and build stronger customer loyalty.

Prior to leading Beyond the Arc, Ramirez served as an executive with Time Warner, where he was responsible for creating and successfully implementing marketing and corporate development strategies.

Ramirez earned a bachelor's degree and master's in Business Administration from the University of California at Berkeley. He as also created and taught courses in business management for UC Berkeley and been a guest speaker at the university's Haas School of Business.

Session: The More the Merrier: Leveraging Open Data Sources to Increase Customer Insights Through Predictive Analytics

 Karl Rexer

Karl Rexer

President

Rexer Analytics

Karl Rexer founded Rexer Analytics in 2002.  He and his teams provide predictive modeling and analytic consulting to clients across many industries.  Recent clients include PwC, Boston Scientific, Redbox, ADT
Security, Interamericana University, MIT, A.S.Watson, and many smaller companies.  In addition to leading client engagements and hands-on data work, Karl is a predictive analytics evangelist, frequently speaking at conferences, colleges, and other events.  He also serves on Advisory Boards for the Business Analytics programs at both Babson College and Bentley University.  Several software companies have sought Karl's input, and in 2008 and 2010 he served on SPSS's (IBM) Customer Advisory Board.  He also served 11 years on the Board of Directors of the Oracle Business Intelligence, Warehousing, & Analytics (BIWA) Special Interest Group.  Since 2007 Rexer Analytics has conducted surveys of analytic professionals,  asking them about their algorithms, tools, behaviors and views.  Summary reports from these surveys are available as a free download from the Rexer Analytics website.


Prior to founding Rexer Analytics, Karl held leadership positions at several consulting firms and two multi-national banks.  Karl holds a PhD from the University of Connecticut.

Plenary Session: Industry Trends: Highlights from the 2015 Data Miner Survey

 Pasha Roberts

Pasha Roberts

Co-Founder and Chief Scientist

Talent Analytics, Corp.

@pasharoberts

Pasha Roberts is chief scientist at Talent Analytics Corp., a company that uses data science to model and optimize employee performance in areas such as call center staff, sales organizations and analytics professionals. He wrote the first implementation of the company’s software over a decade ago and continues to drive new features and platforms for the company. He holds a bachelor’s degree in economics and Russian studies from The College of William and Mary, and a master of science degree in financial engineering from the MIT Sloan School of Management.

Session: A Transaction-Based Approach to Understand Sales Representative Growth, Performance, and Gaming

 Kimberly Scott

Kimberly Scott

Data Scientist

Elder Research

Kim Scott is a Data Scientist at Elder Research who consults with commercial and retail clients to help them address their business needs. She graduated from the University of Evansville with a BS in Physics and Mathematics, and earned a PhD in Astronomy at the University of Massachusetts, Amherst. Prior to joining Elder Research, Kim studied the formation and evolution of galaxies by mining large astronomical data. Some of her successes include developing customized data processing software using advanced analytics for millimeter-wavelength cameras, creating algorithms to identify galaxies from astronomical images, and testing novel calibration techniques to reduce overhead and increase efficiencies for data collection.

Session: Driving Product Improvements and Marketing Efforts through Software Usage Logs

 John Smits

John Smits

Chief Data Officer, Global Business Operations

EMC

As Chief Data Officer for EMC’s Global Business Operations, John is responsible for the generation, processing and analysis of data as a strategic information asset for go-to-market planning and field enlightenment. John leads EMC’s internal Data Science Operations who combine advanced market segmentation techniques; customer data profiling and business analytics to accelerate revenue capture opportunities. John recently served as Senior Director for Advanced Analytics where he launched EMC’s first internal data science organization - successfully leveraging Big Data resources to deliver critical new insights. Prior to joining EMC, John served in senior marketing and analytical roles for Motorola, Aware, Inc. and Lucent Technologies. John has an M.B.A. from Babson College of Wellesley, Massachusetts and a B.S. in Marketing from Bentley College of Waltham, Massachusetts. John enjoys spending time with his family in Stow, Mass. and training for the annual Pan-Mass Cycling Challenge.

Session: Predicting B2B Sales Success

Dr. Patrick Surry

Dr. Patrick Surry

Chief Data Scientist

Hopper

@PatrickSurry

As Chief Data Scientist at Hopper, Patrick Surry analyzes flight data to help consumers make smarter travel choices. Patrick is recognized as a travel expert and he frequently provides data-driven insight on the travel industry and trends.


Patrick’s research and commentary have been featured in outlets such as New York Times, USA Today, Bloomberg Businessweek, TIME, and many others. Patrick also regularly appears on various broadcast stations to offer travel insight and tips.


Patrick holds a PhD in mathematics and statistics from the University of Edinburgh, where he studied optimization based on evolutionary algorithms, following an HBSc in continuum mechanics from the University of Western Ontario.


You can also follow Patrick on Twitter at @PatrickSurry.

Keynote: Buy or Wait? How the Bunny Predicts When to Buy Your Plane Ticket
Session: Applying Next Generation Uplift Modeling to Optimize Customer Retention Programs

 Christopher Wiggins

Christopher Wiggins

Chief Data Scientist

The New York Times

Chris Wiggins is an associate professor of applied mathematics at Columbia University and the Chief Data Scientist at The New York Times. At Columbia he is a member of the Department of Applied Physics and Applied Mathematics, founding member of the Department of Systems Biology, the executive committee of the Data Science Institute (http://datascience.columbia.edu/), and the Institute’s education and entrepreneurship committees. He is also an affiliate of Columbia’s Department of Statistics, an instructor in the Lede program at the Columbia University Graduate School of Journalism, and a founding member of Columbia’s Center for Computational Biology and Bioinformatics (C2B2). He is a co-founder and co-organizer of hackNY (http://hackNY.org), a nonprofit which since 2010 has hosted student hackathons each semester and the hackNY Fellows Program, a structured summer internship at NYC startups, each summer. Prior to joining the faculty at Columbia he was a Courant Instructor at NYU (1998-2001) and earned his PhD at Princeton University (1993-1998) in theoretical physics. In 2014 he was elected Fellow of the American Physical Society and is a recipient of Columbia’s Avanessians Diversity Award.

Keynote: Data Science at The New York Times

 Ryan Williams

Ryan Williams

Director of Analytics

Sidecar

Ryan leads the analytics team at Sidecar, a data driven solution to product based marketing in the online retail space. He has 10 years of experience in the online marketing and analytics fields from his work at Sidecar and eBay Enterprise (formally TrueAction). Ryan is passionate that mathematically predicted marketing decisions are more powerful than those built on intuition. At Sidecar, he is focused on proving the value of predictive analytics in the online marketing space and integrating impactful predictive algorithms into Sidecar’s software. Ryan holds a BS in Mathematics from Dickinson College and a MS is Predictive Analytics from Northwestern University.

Session: Using Predictive Analytics to Drive Successful Product-Based Marketing in e-Commerce Product Listing Ad Channels

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