Predictive Analytics World for Financial Las Vegas 2020
May 31-June 4, 2020 – Caesars Palace, Las Vegas
Product Lead, Machine Learning
Gil serves as the head of Lyft's Machine Learning Platform. Previously he was co-founder of Octarine, a security startup, and VP Product of Reflektion, an e-commerce personalization company, and AppDirect, the largest B2B app marketplace. Gil also spent a few years in product positions at Google in the Ads group, where he helped integrate YouTube and DoubleClick after their acquisition.
Gil Arditi is speaker of the following session:
Chief Data and Analytics Officer
Naveed Asem is the Chief Data and Analytics Officer and Senior Vice President at Donnelley Financial Solutions (DFIN), a $1.2 billion company that provides software and services to support clients with regulatory reporting, filing, and compliance functions globally.
Naveed joined DFIN in 2016 as the head of data and analytics. He now leads a growing team of data architects, engineers, and data scientists who are focused on creating business value from data through the use of modern data management technologies, analytics and machine learning. The team is not only responsible for the implementation of DFINâ€™s enterprise data warehouse and data lakes, but they manage everything from data ingestion and curation, to the delivery of reporting, and filing of artifacts with regulatory bodies in the U.S. and EU.
Naveed Asem is speaker of the following session:
Anasse Bari Ph.D.
Professor of Computer Science
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.
Anasse Bari Ph.D. is speaker of the following session:
Senior Software Engineer
Leslie Barrett is a Senior Software Engineer at Bloomberg LP's Bloomberg Law division specializing in NLP and Machine Learning applied to legal and government text. Before Bloomberg she was Director of Search Technology at The Ladders Inc, an online resource for executive jobseekers and recruiters. Previously, she was Director of Language Technology at the Financial Times where she managed groups creating new online news search products and electronic news alerts. Leslie holds Ph.D. in Computational Linguistics from New York University. She has over 20 published papers in the fields of Natural Language Processing and Information Retrieval and holds 2 patents. She serves on the Program Committees for the International Conference on Computational Linguistics and Intelligent Text Processing and the International Workshop on Big Data for Financial News.
Leslie Barrett is speaker of the following session:
Managing Director, Enterprise Analytics
Jodi Blomberg leads the team that uses data, analytics and data science to understand and measure the events and interactions that make up a client journey as it crosses the enterprise. They connect big data across lots of silos and turn it into visualizations, insights, models and data products to understand and influence client experiences.
She is also responsible for model governance and risk management of data science models across the centralized analytics organization. She has over 15 years of experience in data science and predictive analytics in a variety of industries including software as service fraud solutions, text classification and financial services.
Jodi Blomberg is speaker of the following session:
Senior Vice President
Richard Boire's experience in predictive analytics and data science dates back to 1983, when he received an MBA from Concordia University in Finance and Statistics.
His initial experience at organizations such as Reader’s Digest and American Express allowed him to become a pioneer in the application of predictive modelling technology for all database and CRM type marketing programs. This extended to the introduction of models which targeted the acquisition of new customers based on return on investment.
With this experience, Richard formed his own consulting company back in 1994 which is now called the Boire Filler Group, a Canadian leader in offering analytical and database services to companies seeking solutions to their existing predictive analytics or database marketing challenges.
Richard is a recognized authority on predictive analytics and is among a very few, select top five experts in this field in Canada, with expertise and knowledge that is difficult, if not impossible to replicate in Canada. This expertise has evolved into international speaking assignments and workshop seminars in the U.S., England, Eastern Europe, and Southeast Asia.
Within Canada, he gives seminars on segmentation and predictive analytics for such organizations as Canadian Marketing Association (CMA), Direct Marketing News, Direct Marketing Association Toronto, Association for Advanced Relationship Marketing (AARM) and Predictive Analytics World (PAW). His written articles have appeared in numerous Canadian publications such as Direct Marketing News, Strategy Magazine, and Marketing Magazine. He has taught applied statistics, data mining and database marketing at a variety of institutions across Canada which include University of Toronto, George Brown College, Seneca College, and currently Centennial College. Richard was Chair at the CMA's Customer Insight and Analytics Committee and sat on the CMA's Board of Directors from 2009-2012. He has chaired numerous full day conferences on behalf of the CMA (the 2000 Database and Technology Seminar as well as the 2002 Database and Technology Seminar and the first-ever Customer Profitability Conference in 2005. He has most recently chaired the Predictive Analytics World conferences in both 2013 and 2014 which were held in Toronto.
He has co-authored white papers on the following topics: "Best Practices in Data Mining" as well as "Customer Profitability: The State of Evolution among Canadian Companies." In Oct. of 2014, his new book on "Data Mining for Managers-How to use Data (Big and Small) to Solve Business Problems" was published by Palgrave Macmillian. In March of 2016, Boire Filler Group was acquired by Environics Analytics where his current role is senior vice-president of innovation.
Richard Boire is speaker of the following session:
Senior Quantitative Researcher
Chakri Cherukuri is a senior researcher in the Quantitative Financial Research Group at Bloomberg LP in NYC. His research interests include quantitative portfolio management, algorithmic trading strategies, and applied machine learning. He has extensive experience in scientific computing and software development. Previously, he built analytical tools for the trading desks at Goldman Sachs and Lehman Brothers. He holds an undergraduate degree in mechanical engineering from the Indian Institute of Technology (IIT) Madras, India, and an MS in computational finance from Carnegie Mellon University.
Chakri Cherukuri is speaker of the following session:
Christian Elsasser is speaker of the following session:
Bas Geerdink is responsible for the fast data systems that process and analyze streaming data at ING. He has a background in software development, design, and architecture with broad experience from C++ to Prolog to Scala. He studied artificial intelligence and informatics and has published research on reference architectures for big data solutions.
Bas Geerdink is speaker of the following session:
Head of Responsible Innovation, Global Affairs
Jen Gennai leads Google’s Responsible Innovation team which is responsible for operationalizing Google’s AI Principles, ensuring that Google’s products have fair and ethical outcomes on individual users and the world. Her team works with product and engineering, leveraging a multidisciplinary group of experts in ethics, human rights, user research, racial justice and gender equity to validate that products and outputs align with our commitments to fairness, privacy, safety, societal benefit and more. Before she co-authored the AI Principles and founded Responsible Innovation, Jen worked on machine learning fairness and founded the Ethical ML team in Trust & Safety.
Jen Gennai is speaker of the following session:
Keith Higdon serves as President of ESIS, Inc., with overall management responsibility for this business. He is based in Chicago.
ESIS is one of the industry’s oldest and largest risk management services companies, providing claim and risk management services to a wide variety of commercial clients in the U.S. and globally. ESIS maintains a sharp focus on helping its clients manage their total cost of loss, offering comprehensive and flexible programs and innovative approaches to claims administration. ESIS is committed to achieving measurable results through consistently superior execution, and employing data analytic and predictive modelling capabilities to track progress.
Previously, Mr. Higdon served as Senior Vice President of Partnership Services for ESIS where he oversaw the management and development of client partnerships across all ESIS lines of business. In addition, he has accountability for new client implementations, ESIS University, ESIS construction practice, and ESIS global initiatives.
Mr. Higdon has 20 years of industry experience. He began his career in consulting conducting and managing auditing, program evaluation, and program design projects for workers compensation and integrated disability management programs to large employers and service providers. He left consulting for the third-party administrator (TPA) space where he held a variety of positions under information technology and client services developing and delivering differentiated products and services to clients. With a strong focus on information delivery, his previous TPA experience culminated in the management of four departments focusing on client reporting, predictive modeling, client-facing system enhancement and support, and loss control consulting and OSHA administration. Mr. Higdon holds two Bachelor of Science degrees in the social sciences from Northern Illinois University and a master’s degree in information technology and management from Illinois Institute of Technology. He is a board member, and former Chairman, for the Center for Employee Health Studies associated with the School of Public Health at the University of Illinois at Chicago. Mr. Higdon supports industry development through participation in regional and national conferences and has published on key topics including integrated disability management, the data lifecycle, and predictive modeling over the years. He is also a volunteer mentor and guest speaker at YearUp, a community college based program for economically disadvantaged students.
Keith Higdon is speaker of the following session:
Abhishek Joshi ‘AJ’
Abhishek Joshi ‘AJ’ is a Sr. Director in Visa’s consulting & analytics group. He is responsible for helping financial institutions with improving growth and profitability through advanced analytics techniques. AJ has diverse experience in employing analytics to solve business problems across multiple industries – Manufacturing & Engineering, Financial Services and Telecom.
Abhishek Joshi ‘AJ’ is speaker of the following session:
Chief Data Office
Sravan Kasarla is speaker of the following session:
Associate Professor of Analytics
A Teaching Associate Professor in the Institute for Advanced Analytics, Dr. Aric LaBarr is passionate about helping people solve challenges using their data. There he helps design the innovative program to prepare a modern workforce to wisely communicate and handle a data-driven future at the nation's first master of science in analytics degree program. He teaches courses in predictive modeling, forecasting, simulation, financial analytics, and risk management.
Previously, he was Director and Senior Scientist at Elder Research, where he mentored and lead a team of data scientists and software engineers. As director of the Raleigh, NC office he worked closely with clients and partners to solve problems in the fields of banking, consumer product goods, healthcare, and government.
Dr. LaBarr holds a B.S. in economics, as well as a B.S., M.S., and Ph.D. in statistics — all from NC State University.
Aric LaBarr is speaker of the following session:
Director of Data Science, US EOIT Advanced Analytics & AI
Richard Lee is Director of Data Science for John Hancock, the U.S. division of Toronto-based Manulife.
Richard leads the Advanced Analytics & AI group, which supports operations decision analytics across all U.S. businesses.
In his current role, Richard finds opportunities for efficiencies in Life Insurance as well as Long Term Care Insurance operations. Much of his focus is on innovation to enhance the relevance and understanding of analytics and its impact on operations decision-making.
Prior to his current role, Richard has spent 15 years at John Hancock in various analytics roles.
Richard Lee is speaker of the following session:
AI and Data Science Center of Excellence Leader, Workplace Investing
Victor S.Y. Lo is a seasoned Big Data, Marketing, Risk, and Finance leader with over 25 years of extensive consulting and corporate experience employing data-driven solutions in a wide variety of business areas, including Customer Relationship Management, Market Research, Advertising Strategy, Risk Management, Financial Econometrics, Insurance, Product Development, Transportation, and Human Resources. He is actively engaged with causal inference and is a pioneer of Uplift/True-lift modeling, a key subfield of data science.
Victor has managed teams of quantitative analysts in multiple organizations. He currently leads the AI and Data Science Center of Excellence, Workplace Investing at Fidelity Investments. Previously he managed advanced analytics/data science teams in Personal Investing, Corporate Treasury, Managerial Finance, and Healthcare and Total Well-being at Fidelity Investments. Prior to Fidelity, he was VP and Manager of Modeling and Analysis at FleetBoston Financial (now Bank of America), and Senior Associate at Mercer Management Consulting (now Oliver Wyman).
For academic services, Victor has been a visiting research fellow and corporate executive-in-residence at Bentley University. He has also been serving on the steering committee of the Boston Chapter of the Institute for Operations Research and the Management Sciences (INFORMS) and on the editorial board for two academic journals. He is also an elected board member of the National Institute of Statistical Sciences (NISS). Victor earned a master’s degree in Operational Research and a PhD in Statistics, and was a Postdoctoral Fellow in Management Science. He has co-authored a graduate level econometrics book and published numerous articles in Data Mining, Marketing, Statistics, Analytics, and Management Science literature, and is completing a graduate level book on causal inference in business.
Victor Lo is speaker of the following session:
Carrie Lu Ph.D.
Senior Data Scientist
Carrie (Caimei) Lu is a Senior Data Scientist at Safety National. She has over eight years of experience in using machine learning to generate insights from huge amounts of data, and using data science technologies to solve challenging business problems where data holds the key. At Safety National, Carrie Lu works with insurance business stakeholders on developing predictive models that can flag potential high risk and help the company reduce cost on long-term developmental claims. Carrie Lu holds Ph.D. in Information Science from Drexel University. She has over 15 published papers in the fields of Data Mining and Machine Learning.
Carrie Lu Ph.D. is speaker of the following session:
Andreas is working as a Quantitative Researcher at Goldman Sachs Quantitative Execution Services, with an emphasis in machine learning techniques for execution algorithms. Andreas has received a PhD in Information Engineering at the University of Cambridge, focusing on the interface of stochastic control theory and Bayesian machine learning, where he developed graph theoretic tools for predicting the shapes of the probability distributions to arise in the observable time-series due to the underlying non-linear stochastic interconnections. Andreas’ teaching experience included several engineering undergraduate courses, including Inference and Machine Learning, Linear Algebra, Probability, Control and Signal Processing. During his PhD, he has also worked at Informetis Europe as a Machine Learning Algorithm Engineer, developing efficient Bayesian inference techniques for smart electricity meter applications. Andreas also holds a BA and an MEng degree in Electrical and Information Sciences from Trinity College, University of Cambridge, during which he has received the G-Research and The Technology Partnership (TTP) awards, while his Master’s thesis was done in collaboration with British Cycling, developing a racing cyclist fitness predictor.
Andreas Petrides is speaker of the following session:
Global Head of Risk Strategy and Analytics
Alex Sanchez is speaker of the following session:
Eric Siegel, Ph.D., founder of the Predictive Analytics World conference series and executive editor of The Predictive Analytics Times, makes the how and why of predictive analytics understandable and captivating. He is the author of the award-winning Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, a former Columbia University professor who used to sing to his students, and a renowned speaker, educator, and leader in the field.
Eric has appeared on Bloomberg TV and Radio, Business News Network (Canada), Fox News, Israel National Radio, NPR Marketplace, Radio National (Australia), and TheStreet. He and his book have been featured in Businessweek, CBS MoneyWatch, Contagious Magazine, The European Business Review, The Financial Times, Forbes, Forrester, Fortune, Harvard Business Review, The Huffington Post, The New York Review of Books, Newsweek, Quartz, Salon, Scientific American, The Seattle Post-Intelligencer, The Wall Street Journal, The Washington Post, and WSJ MarketWatch. Follow him at @predictanalytic.
Eric Siegel is speaker of the following session:
Michael Steliaros is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading as well as managing the bank's relations with the quantitative client base. Previously, Michael held a variety of senior roles at BofAML in London and New York, most recently running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, and an MSc and PhD in Finance from City University (CASS) Business School in London
Michael Steliaros is speaker of the following session:
Vice President, Data Science Manager
Nathan Susanj is a data scientist on the Wells Fargo Enterprise Analytics and Data Science team. He leads a small team as head of Natural Language Processing (NLP) and Speech Capabilities Development, where he is focused on building out Wells Fargo's capabilities in areas related to NLP, deep learning and data science product design. Nathan holds a Masters in Predictive Analytics from Northwestern University and is working on his second Masters in Computer Science from Georgia Tech. He has been with Wells Fargo for the past five years and worked in marketing analytics prior to his current role.
Nathan Susanj is speaker of the following session:
Chief Risk and Data Analytics Officer
William (Bill) Wilkins is a multi-purpose actuary for the Safety National Casualty Corporation(SNCC). He is a CERA, FCAS, ASA and MAAA. While his main focus is on Enterprise Risk Management and Predictive Analytics, Bill has experience in pricing insurance, reinsurance, credit risk products, risk management, reserving and broker management. He is currently Co-Chair of the SNCC Data Analytics Committee. The Data Analytics Committee is a cross-functional group tasked with all aspects of data for SNCC. The Committee works on data to be collected, how it is collected, where it is collected from, how it stored, standards and practices of usage, etc. This includes the populating items like benchmarking reports or how best to create and use predictive analytics. The goal is to establish a process that is repeatable and adaptable so SNCC can deliver both internally and externally.
William WIlkins is speaker of the following session: