October 29-November 2, 2017
New York
The premier machine learning conference
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Speakers



Dr. Gary Anderberg

Dr. Gary Anderberg

SVP of Claim Analytics Product Management

Gallagher Bassett

Gary Anderberg has worked in developing predictive analytic applications for workers' compensation insurance since 2007. He is a recognized expert in the use of PA outputs for guiding the handling of complex claims to drive improved claim outcomes. He is the "godfather" of the Waypoint system and its key role in improving overall decision making and the more effective use of claim resources at Gallagher-Bassett. He will speak to the business case for a system like Waypoint and the corporate cultural and practice issues involved in socializing potentially complex PA system outputs with deeply entrenched work patterns at the end user level. He knows first-hand how the most brilliant PA applications can founder when output and practice cultures clash.

Session:  Workers' Compensation Litigation Propensity Predictive Analytics

 Anasse Bari, Ph.D.

Anasse Bari, Ph.D.

Professor of Computer Science - Director of the AI and Predictive Analytics Lab

New York University

Anasse Bari is a professor of computer science and director of the Predictive Analytics and AI research lab at New York University. Prof. Bari teaches computer science and leads a multidisciplinary research team that designs specialized Artificial Intelligence to help solve problems in healthcare, business, finance, politics and social good.

Session: Wall Street and the New Data Paradigm

 Tracie Coker Kambies

Tracie Coker Kambies

Principal | Retail Technology and Analytics

Deloitte

Tracie is the U.S. Retail  Sector Analytics and IoT Lead for Deloitte bringing breadth and depth of services to the Retail market in the areas of Technology Strategy, Analytics & Information Management, Cloud and IoT solutions. She is the National  Analytics & Information Management & Analytics Alliance Leader, and has seventeen years of business consulting experience focused on retail, consumer and industrial products clients.  Tracie also leads creation of the Retail Internet of Things strategy and solution development.


Tracie has deep experience in information management & analytics, master data management and governance, and data integration projects .  She manages and delivers complex global data & analytics projects. She bring business and IT together to deliver analytics and data strategies,  data quality, governance, and drive insights at the speed of business. Tracie has strong technology delivery experience and communication skills combined with a proven leadership record in the Technology and Analytics arena.

Expert Panel:  Women in Predictive Analytics: Opportunities and Challenge

Shared panel session with PAW Business


 Kevin Colberg

Kevin Colberg

Director of Analytic Engineering

Dealertrack (subsidiary of Cox Automotive)

Kevin is an IT Professional with extensive experience implementing, aligning and governing business intelligence and data analytics solutions, with 15 years of BI and Analytic experience. Strengths include technology and team leadership, strategic planning, business analytics, project management and customer communication, combined with a deep technical background and ability to be effective in strategic and tactical initiatives.

Session: Data Brokering for the Lender Community - Building an analytics based product using composite data

 Tom Doris

Tom Doris

CEO

OTAS Technologies

Tom is co-founder and CEO of OTAS Technologies. He is responsible for product development of OTAS, the market data analytics platform, and OTAS TradeShaper, the real-time microstructure analysis and trading optimization platform, which are used by the top global institutions and hedge funds worldwide to enhance decision making and improve performance.  


Previously, he worked on optimized execution and microstructure analytics in the quant trading group at Marshall Wace, and led the exotic equity derivatives quant development team at Bear Stearns/JP Morgan. 


Tom spent 5 years as a research and design engineer at Intel, where he received a patent for his work on compiler optimizations targeting non-uniform memory architecture multicore processors. He holds a Ph.D in computer science for work in computational neuroscience.

Session: Enhancing The Human Trader with Predictive Analytics and Context Sensitive Data

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, Washington DC, and London. 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.

Special Featured Session: How to Tell if Your Market Timing System Will Work: A New Measure of Model Quality

Workshop:  The Best and the Worst of Predictive Analytics: Machine Learning Methods and Common Data Science Mistakes


 Dongyang Fu

Dongyang Fu

Data Scientist

Concord Advice

Dongyang Fu is a data scientist at Concord Advice. He has more than two years experience working in risk related fields. He actively attempts to apply advanced data mining techniques in solving business problems. Prior to joining Concord Advice, he was an analytic consultant in EXL Services focused on small business lending. Dongyang holds a Masters of Science in Operations Research from Columbia University and B.S. in Industrial Engineering from Purdue University.

Session:  Improving Credit Scoring with Hierarchical Bayesian Modeling

 Aaron Goldenberg

Aaron Goldenberg

Independent Quantitative Consultant

Aaron is an independent quantitative consultant developing applications of TensorFlow for algorithmic trading. He holds advanced degrees in math and law and has worked previously with a structured products group at Societe Generale as well as a number of hedge funds developing algorithmic trading strategies.

Session: Predictive Modeling using Deep Learning with TensorFlow

 James Gottshall

James Gottshall

Vice President, Strategic Analytics

XL Catlin

James joined XL Catlin in January 2017 as a Vice President and Business Solutions Consultant on the Strategic Analytics team. He is responsible for leading large and complex analytics projects that enhance decision-making processes and that add tangible business value. James liaises with business leaders, data engineers, and data scientists to create highly impactful business solutions that drive behavioral changes. Prior to joining XL Catlin, James worked at Selective Insurance as an Assistance Vice President of Analytics Strategy. In that role, he was responsible for creating and subsequently executing the analytics strategy to infuse a culture of analytics across the entire organization. James also served as an Assistant Vice President of Claim Analytics Integration at Chubb, where he led the integration efforts within claims advanced analytics.

James earned his B.S. degree in mathematics from Pennsylvania State University. He also serves the United Way of Northern NJ as a Board Trustee.

Session: Model Deployment - If You Build It, Will They Come?

 Michael Grandy

Michael Grandy

AVP, Data Science

MetLife

Mike leads the advanced analytics teams that support MetLife's U.S. Business, providing predictive and prescriptive models for Group Benefits, Auto and Home Insurance, and other business areas.  A thirty year veteran in the insurance industry, Mike has spent the last 17 years developing and deploying models in a wide variety of insurance processes, including underwriting, pricing, claims and claim fraud, marketing, customer service and retention, and operations.  Mike holds a B.A. degree in Linguistics from Bethel University.

Session: Pragmatic Analytics for Financial Services

 Robert M. Horrobin

Robert M. Horrobin

AVP of Advanced Analytics and Planning, Retirement Solutions Division

Pacific Life

Rob is an experienced change agent and leader of quantitative practices, specializing in the use of data and analysis to help organizations navigate periods of great change. As the AVP-Advanced Analytics and Planning, Rob is focused on analytics and data strategy for the Retirement Solutions Division of Pacific Life. Prior to joining Pacific Life, Rob oversaw the Insurance Operations Optimization & Decision Analytics practice at John Hancock. Rob started this internal consulting practice in 2015 after taking on increasing roles of responsibility in Reinsurance Finance, Corporate Development/Strategy, and Analytics. Before joining John Hancock in 2008, Rob had extensive experience in the shipbuilding industry with a focus on optimizing design for construction efficiency. Rob holds a Bachelor of Mechanical Engineering from the University of Delaware, as well as a Masters of Business Administration from Boston University.

Session: Analytics Capstone Projects: Embedding Analytics Throughout Your Organization

 Krishna Kallakuri

Krishna Kallakuri

President

diwo – Loven Systems

Krishna Kallakuri is President & founder of Loven Systems, the creators of diwo®.  Krishna’s visionary leadership and delivery of transformational BI and Analytics initiatives to leading Fortune 500's has landed the practice he has founded on the Midwest’s Fastest-Growing list. With 20 years of expertise in technology and executive management, Mr. Kallakuri’s passion for advanced analytics, cognitive technologies, and artificial intelligence has led to pioneering work—most recently the launch of diwo®, which was developed from the ground up as a “business-first” platform to address the adoption issues common with other transformative initiative

Session:  Driven Enterprise; Turning Business On Its Head

 Vishwa Kolla

Vishwa Kolla

AVP

John Hancock Insurance

Vishwa heads Advanced Analytics function at John Hancock Insurance. He is passionate about combining math and data to drive Business outcomes. Towards this end, he led several engagements that use ML and AI methods across 6 industries and in over a dozen F100 firms.


Vishwa is a thought leader and regularly speaks at conferences on a variety of topics - Analytics Architecture & Strategy, Internal and 3rd Party Data, Big Data Best Practices, Advanced Methods - opportunities & Pitfalls, AI-Led transformations, C[A, AI, D] O series - operating models, Underwriting Risk Analytics, Marketing Analytics and Mix Modeling, Fraud Analytics.


Vishwa received his MBA from Carnegie Mellon University, an MS from U. Denver and BS from BITS Pilani, India.

Session:  Black Box vs. White Box, Single Model vs. Stratified - Who What Where When Why How

 Joe Kruse

Joe Kruse

Senor Manager, Data Analytics

Ernst & Young LLP

Joe is a New York-based senior manager in EY's Data and Analytics (D&A) practice. He has thirteen years of experience helping detect, capture and sustain value through the use of advanced analytics.  He has assisted his clients in projects to identify future revenue potential, better detect hidden signals within everyday activity, maximize operational efficiency, meet regulatory deadlines, better leverage tools and have a greater understanding of available data both within and outside their organizations.

Session: Growing Customer Relationship Value through Analytics

 Julia Minkowski

Julia Minkowski

Product Lead

Walmart Global Tech

Julia is a Fraud Detection and Risk Management expert, innovator, startup advisor, mentor and a speaker. Currently she is a Product lead at Walmart Global tech focusing on mitigating fraud for Mobile payments and Marketplace. Prior to this, Julia worked with Fiserv, Signifyd, ThreatMetrix, LexisNexis Risk Solutions and helped Fortune 50 Tech and E-Commerce companies such as Microsoft, Intuit, Ebay, Chegg and others to save millions of dollars in fraud losses.

Julia holds a Bachelor’s Degree in Sociology and Geography from the Hebrew University of Jerusalem, Software Programming Certificate from John Bryce Institute, MBA from HaUniversita Ha-Ptuha of Israel, and Strategic Decision and Risk Management Diploma from Stanford University.

Keynote: Real-Time Fraud Detection: Strategies for Speed and Actionability

Expert Panel:  Women in Predictive Analytics: Opportunities and Challenges

 Stephen Morse

Stephen Morse

Advisor

Neudata

Stephen consults in the areas of FinTech and Big and Alternative Data, including as an advisor to Neudata - a firm specializing in alternative data discovery and intelligence. Previously, as former Head of Global Financial Data Partnerships at Twitter, Stephen was responsible for all business with hedge funds, asset managers, banks, FinTech partners, platforms and other financial institutions.  He joined via acquisition of Gnip, where he opened and ran the New York office. Stephen has a long career in entrepreneurial, disruptive businesses, especially in and around data, hedge funds, FinTech and business information services, including with firms that were acquired by, or are now a part of Barra/MSCI, Dow Jones, KCG and Twitter. 

Session: Leveraging Alternative Data Sources to Gain a Critical Competitive Advantage

 Mei Najim, CSPA

Mei Najim, CSPA

Applied Analytics Manager, Compliance

HSBC

Mrs. Mei Najim is the Co-Chair of PAW for Financial Conference.  

Mei Najim currently works as an Applied Analytics Manager at HSBC and teaches part-time as a Data Analytics Lecturer at University of Chicago. Mei has over 18 years of hands-on analytics experience in banking (collections, agent performance, and financial crime), insurance (claim management, underwriting, pricing, reserving, and catastrophe risk management), and consulting.

Since 2007, Mei has mainly been working, leading, and implementing various large scale data analytics and predictive analytics projects to develop analytics capability for financial organizations. She has extensive statistics, machine learning, and data mining experience dealing with large and complex data sets.  She is an analytics thought leader with a positive influence and a clear vision for how analytics can transform business strategy through techniques, communication, and leadership to devise innovative data-driven solutions. 
Mei has been a frequent speaker at various industry conferences to share her expertise in predictive analytics, machine learning, and data science. She holds a BS in actuarial science from Hunan University and two MS degrees in applied mathematics and in statistics, from Washington State University. She is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.

Session: Workers' Compensation Litigation Propensity Predictive Analytics

 Yulin Ning

Yulin Ning

Senior Director in Global Decision Management

Citigroup

Yulin Ning is a Senior Director in Global Decision Management, a global strategy and analytic division in Citi's Global Consumer Bank. He currently leads next generation analytics efforts within Platform and Capability function, acting as a chief data scientist, aiming to accelerate global adoption of big data and machine learning for creative business solutions. He developed expertise in digital (clickstream), text mining, voice analytics, big data, and machine learning. His most recent interests are on deep learning and artificial intelligence.


Over 18 years at Citi, Yulin has been actively involved in building some of the key decision management disciplines in the areas of price management, stress test capabilities, optimization, big data / machine learning roadmap, and data scientist disciplines. He worked with a range of financial and technology companies, vendors, and universities specializing in analytics and emerging technologies. He holds a Ph.D. in Agricultural Economics.

Session: Predictive Analytics in Today's Era of Digital, Machine Learning, and AI: A Financial Industry Perspective

 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.

Keynote: Chatbots, Robo-Advisors, and AI, Oh My! Predictive Analytics and Machine Learning Case Studies for Financial Services and FintechBA

 Anne G. Robinson

Anne G. Robinson

Chief Strategy Officer

Kinaxis

@agrobins

As Chief Strategy Officer, Anne is responsible for accelerating Kinaxis strategy development to add further value to customers. She and her team collaborates closely with customers, external stakeholders and the rest of the senior executive team to drive the strategic roadmap, thought leadership and identify emerging technologies and new industry opportunities.


A proven leader in analytics and digital transformation, with expertise in operations, supply chain, and strategy, Anne has extensive experience in managing supply chains for complex, global organizations. As Executive Director, Global Supply Chain Strategy, Analytics and Systems at Verizon, Anne was responsible for the strategic vision of the company’s global end-to-end supply chain, driving excellence through world-class data-analytics, process innovation and employee empowerment. Before Verizon, Anne spent several years at Cisco where she was responsible for managing advanced analytics, business intelligence and performance management teams.


Anne is a past president of INFORMS (the Institute for Operations Research and Management Sciences), a seasoned industry speaker and has served on several advisory boards. Originally from St. John's, Newfoundland and Labrador, Anne has a BScH from Acadia University, MASc from the University of Waterloo and an MSc and PhD in Industrial Engineering from Stanford University.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenge

Shared panel session with PAW Business

 Wen Shi

Wen Shi

Data Scientist

Concord Advice

Wen Shi is a data scientist at Concord Advice. He is focused on risk management solutions using advanced statistical methodologies as well as ML techniques. Prior to joining the company, he worked as a financial analyst in Harvard Management Associates Inc., and provided risk measurements for NASDQ listing and pipe financing. Wen holds a Master's degree in Financial Statistic and Risk Management from Rutgers University and a bachelor's degree in Economics from Shanghai University of International Business and Economics. 

Session:  Improving Credit Scoring with Hierarchical Bayesian Modeling 

 Seth Stephens-Davidowitz

Seth Stephens-Davidowitz

Author and NYTimes Opinion Writer

Seth Stephens-Davidowitz is a New York Times op-ed contributor, a visiting lecturer at The Wharton School, and a former Google data scientist. He received a BA in philosophy from Stanford, where he graduated Phi Beta Kappa, and a PhD in economics from Harvard. His research—which uses new, big data sources to uncover hidden behaviors and attitudes—has appeared in the Journal of Public Economics and other prestigious publications. He lives in New York City.

Session: Google Searches and the Market

 Mike Thurber

Mike Thurber

Principal Scientist

Elder Research

Mike Thurber is the Lead Data Scientist in Elder Research's Commercial Analytics Group working across multiple teams and industries – including finance, retail, energy, and telecom – to deliver information products that drive business value.  Mike’s primary focus is healthcare and insurance, where his projects range from predicting extreme payouts on long-term care claims, and identifying healthcare provider fraud, to measuring the effect of Cesarean delivery on infant health. His expertise in collaboration, data exploration, predictive modeling and rigorous testing, and in remediating the selection bias common to analytic algorithms, creates confidence in the actions recommended by the analytic products of his team.


Mike earned a BS degree in Chemical Engineering from Brigham Young University and a Master's degree in Statistics from Virginia Commonwealth University. For the last four years, Mike has been teaching principles and best practices of predictive modeling to a broad audience of emerging data scientists.

Session: Analytics Capstone Projects: Embedding Analytics Throughout Your Organization

 Li Yang

Li Yang

Senior Data Scientist

Plymouth Rock

Li Yang is a senior data scientist at Plymouth Rock Assurance of New Jersey, an automobile and homeowner insurance firm with operations throughout the Northeast U.S. 

For the past six years, he has worked on a variety of insurance-related assignments including loss modeling, marketing and lifetime value, underwriting, and claims analytics. His expertise lies in the detection of fraud and abuse through predictive analytics. Prior to his foray into the world of data science, Li spend five years in various technical roles at financial services and high tech firms.

Li holds an MS in Applied Statistics from California State University - Long Beach and a BS in Computer Engineering from the University of Michigan - Ann Arbor. 

Session: How to Prevent Medical Abuse in Automobile Injury Claims Through Predictive Analytics

 Pallavi Yerramilli

Pallavi Yerramilli

Senior Product Manager

The Trade Desk

Pallavi Yerramilli is a Senior Trading Specialist at The Trade Desk, a global technology platform for buyers of advertising.  In her role, Pallavi manages a diverse portfolio of programmatic agency clients, working closely with them to optimize and drive performance for their campaigns. In addition, she partners closely with the analytics team at The Trade Desk to build data driven tools to enhance performance based on her clients' needs. Pallavi has a background in electrical engineering and worked as a fixed income trader prior to joining The Trade Desk.

Expert Panel: Women in Predictive Analytics: Opportunities and Challenges                                 


Shared panel session with PAW Business



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