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

Speakers



Dr. Gary Anderberg

Dr. Gary Anderberg

SVP of Claim Analytics Product Management

Gallagher Bassett

Gary is a recovering academic with a BA from Pomona College and an MA and a PhD from Stanford University. He moved from college and university teaching into management consulting in 1976 and later joined one of his clients, a TPA, as their first vice president of data processing. He formed and later sold his own TPA then joined Travelers as part of the team that built one of the first managed care programs for workers compensation. After a stint at Zenith National as one of the designers of the SinglePoint twenty four hour program, he joined Prudential's Group Insurance operation to develop integrated disability management. After retiring from Prudential, Gary joined Broadspire to develop the e-Triage claim modeling system. He was recruited by Gallagher Bassett in 2013 to drive research and development into new technologies to improve outcomes.

Session:  Workers' Compensation Litigation Propensity Predictive Analytics

 Anasse Bari

Anasse Bari

Professor of Computer Science

New York University

Anasse Bari (Ph.D.) is data mining expert and a university professor of computer science at NYU who has many years of predictive modeling and data mining experience. Bari has recently worked closely with leadership of the World Bank Group as a data scientist where he was leading the design of enterprise data analytics projects. Bari is the co-author of the book Predictive Analytics for Dummies, Wiley.

Session: Wall Street and the New Data Paradigm

 Tracie Coker Kambies

Tracie Coker Kambies

Principal | Retail Technology and Analytics

Deloitte Consulting LLP

The U.S. Retail Sector Technology Lead for Deloitte bringing breadth and depth of services to the Retail market in the areas of Technology Strategy, Data &Analytics, and Cloud solutions. Also, the National Information Management & Analytics Learning Leader, and has seventeen years of business consulting experience primarily focused on retail, consumer and industrial products clients. 

Co-leads creation of the Retail Internet of Things strategy & solution development. Bring more than 10+ years of experience in Information Management & Analytics focusing on analytics strategy, organization change, master data management, governance, quality and data integration services. With strong technology delivery experience and communication skills combined with a proven leadership record across the technology landscape. 

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

Dr. John Elder

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 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

Session: Pragmatic Analytics for Financial Services

 Robert M. Horrobin

Robert M. Horrobin

AVP- Head of Operations Optimization & Decision Analytics

John Hancock

Rob oversees 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

Prior to founding diwo, Krishna was a founding member of DataFactZ, one of the fastest-growing analytics company in the Midwest. He brings more than 15 years of expertise in the IT industry as well as senior management experience. Krishna has a strong passion for delivering unique business solutions that leverage global delivery model.

Session:  Driven Enterprise; Turning Business On Its Head

 Vishwa Kolla

Vishwa Kolla

Head of Advanced Analytics

John Hancock Insurance

Vishwa is the head of Advanced Analytics (AA) at John Hancock Insurance (JHI). AA at JHI involves Descriptive, Predictive, Prescriptive, Nudge, Cognitive and Experimental Analytics.

He is a seasoned leader, speaker, collaborator, mentor and a coach in several areas including Advanced Analytics, Data Science, Big Data and in Communication. He oversees the transformation of John Hancock and continues to turn it into an Data, Analytics, Insight, Model and Action rich organization.

Vishwa helped F5-500 companies on a variety of problems using Predictive Analytics as a means. Select clientele includes Deloitte, Walmart, Caterpillar, AIG, AT&T, Cablevision, HP, Cardinal Health and Orlando Health, IBM, and Sun Microsystems (now Oracle).

Vishwa has an 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

Risk Analytics Manager

Signifyd

Julia is an accomplished professional with experience in Software Development, Business Intelligence, Risk Management and Data Analysis in both large corporate environments and start-ups. Currently she is a Principal R&D in Fraud Analytics at Signifyd, saving millions in fraud for global E-Commerce. Prior to this, Julia held various positions at Telecom and Banking/Financial Industry such as Fiserv and Verizon Wireless, evolving from managing the Billing Operations through Software Development, Analysis and Reporting, Data Warehouse into Predictive Analytics in Identity Fraud Detection. 

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 Certificate from Stanford University. She is native of Russia and is based in the Silicon Valley.

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

Mei Najim

Director

Gallagher Bassett

Mrs. Mei Najim is currently the Director of Advanced Analytics at Gallagher Bassett. She is responsible for leading advanced analytics capability development. Mrs. Najim has over 10 years of analytics experience in both personal and commercial line in the areas of predictive analytics, claim analytics, catastrophe risk analytics, actuarial reserving, and actuarial pricing analytics in the Property & Casualty insurance industry. She has presented in industry conferences to share her paper and expertise in predictive analytics. She holds a Bachelor of Science in Actuarial Science from Hunan University and two separate Master of Science degrees, in Applied Mathematics and in Statistics from Washington State University. Mei is a member of the American statistical Association.

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

Executive Director, Strategy, Analytics and Systems

Verizon

@agrobins

Anne G. Robinson is the Executive Director of Global Supply Chain Strategy, Analytics and Systems, at Verizon, a Fortune 15 company and leading provider of wireless, fiber-optic and global internet networks and services. She is responsible for the overarching strategic vision across Verizon's end-to-end supply chain which includes the wireless consumer supply chain, network supply chain, video and internet supply chain as well as global sourcing and procurement. Additionally, her team drives supply chain excellence through world class data-analytics, process innovation, and employee empowerment to achieve a holistic, collaborative and customer centric supply chain organization, that results in improved product life cycle management, working capital optimization, and shareholder value.

Prior to joining Verizon Wireless, Anne spent several years with Cisco Systems, a high tech networking company, where her responsibilities included managing advanced analytics, business intelligence, and performance management teams across the supply chain. As the driving force for many foundational and cross-functional process innovations, she helped establish Cisco's presence and recognition as a leader in business intelligence and analytics, including being inducted into the balanced scorecard hall of fame.

Anne is originally from St. John's, Newfoundland, Canada. She has a Bachelor of Science with Honours in Mathematics from Acadia University, a Master of Applied Science in Management Science from University of Waterloo and a Masters and PhD in Industrial Engineering from Stanford University.

Anne is a Past President of INFORMS (the Institute for Operations Research and the Management Sciences), a professional organization focused on applying advanced analytical theory and practice for making better business decisions. She is a popular industry speaker and has served on several advisory boards including the advisory board for the Stevens Institute of Technology Masters Of Science in Business Intelligence & Analytics. A constant champion for analytics, Anne is the founding editor of INFORMS Editor's Cut, an online multimedia collection examining important topics in operation research and analytics. A frequent tweeter, you can follow Dr. Robinson @agrobins.

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 

 Michael Thurber

Michael Thurber

Lead Data 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 Trading Specialist

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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