Predictive Analytics World for Financial 2021
May 24-28, 2021 – Livestreamed
Specialist, Data Science
Muneeb Alam is a data science specialist at McKinsey & Company. He has experience in the public and social sector, healthcare, energy and basic materials. He holds a B.A. in astrophysics from Columbia University and an MSc. in business analytics from Imperial College Business School.
Muneeb Alam is speaking in the following session:
Bala Venkatram Balantrapu
Experienced Data Scientist with a demonstrated history of working in the insurance industry. Skilled in Machine Learning, Databases, Big Data Analytics, Big Data, Python, R, PySpark and Tableau. Strong engineering professional with a Master's degree focused in Computer Science from University of North Carolina at Charlotte.
Bala Venkatram Balantrapu is speaking in the following session:
SAS Senior Data Scientist.
Robert is a Senior Data Scientist at SAS where he builds end-to-end artificial intelligence applications. He also researches, consults, and teaches machine learning with an emphasis on deep learning and computer vision for SAS. Robert has authored a book on computer vision and has developed several professional courses on topics including neural networks, deep learning, and optimization modeling. Before joining SAS, Robert worked under the Senior Vice Provost at North Carolina State University, where he built models pertaining to student success, faculty development, and resource management. Robert also started a private analytics company while working at North Carolina State University that focused on predicting future home sales. Prior to working in academia, Robert was a member of the research and development group on the Workforce Optimization team at Travelers Insurance. His models at Travelers focused on forecasting and optimizing resources. Robert graduated with a master’s degree in Business Analytics and Project Management from the University of Connecticut and a master’s degree in Applied and Resource Economics from East Carolina University.
Robert Blanchard is speaking in the following session:
John Elder Ph.D.
Founder & Chair
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.
John Elder Ph.D. is speaking in the following session:
Vladimir Iglovikov Ph.D.
Senior Computer Vision Engineer, Level5, Self-Driving Division
Vladimir Iglovikov Ph.D. is speaking in 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 speaking in the following session:
Senior Data Scientist
Ian Knopke recieved his Ph.D. in Computer Science from McGill University, specializing in music search systems. He also worked as a researcher at academic institutions in the US and the UK before joining the BBC as their first data scientist, to work on applied R&D projects for TV, Radio, Sport, News, and the World Service Group. He later worked on data science problems for the Financial Times, Springer Nature, and Elsevier, as well as a couple of AI startups specializing in NLP. Ian joined Thomson Reuters as a Senior Data Scientist in the Reuters Applied Innovation group in 2020 and has also taken on an additional role as a new father in March.
Ian Knopke is speaking in 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 speaking in 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 speaking in the following session:
Principal & Senior Consulting Actuary, ASA
Syed Mehmud, ASA, MAAA, FCA, is a Principal and Senior Consulting Actuary in the Denver office of Wakely. Syed is a recognized expert on risk adjustment and actuarial applications of predictive modeling. Through the combination of large scale actuarial projects and developing popular product offerings, Syed has served most health plans in the United States in some capacity. He has worked on a variety of healthcare related projects, particularly involving the application of risk adjustment tools and implementation of risk adjustment methodologies.
Syed has worked on risk adjustment with clients in Medicare, Medicaid, and Commercial settings. His recent work includes a large-scale actuarial consulting engagement where the Wakely team simulated the HHS risk adjustment methodology in over 30 individual and small group markets across the United States. His other works include the conception and development of the Wakely Risk Assessment (WRA) model, advanced Risk Score Optimization (RSO) analytics, the Wakely RAPID program, and the Wakely Risk Insight (WRI) program.
Most recently, Syed and his team have executed an on-going national-scale project aimed at understanding the drivers of success and challenges in the Affordable Care Act (ACA) program. The Wakely Risk Insight – National Reporting (WRINR) project is a unique lens on the ACA program in that it uses detailed data on millions of ACA lives in order to uncover insights related to succeeding in this program.
Syed co-authored (with Ross Winkelman) the 2007 Society of Actuaries' study on the comparative assessment of risk assessment models. Syed led a 2012 Society of Actuaries’ study on Uncertainty in Risk Adjustment. His other major published works include Society of Actuaries research project titled 'Non-Traditional Predictors in Risk Assessment' (SOA, 2013), and Risk Scoring in Health Insurance – A Primer (SOA, 2016). He is also in the process of writing a book on predictive modeling.
Syed Mehmud is speaking in the following session:
CSPA, Founder and Lead Data Scientist
Advanced Analytics Consulting Services, LLC
Mrs. Mei Najim, CSPA, Founder and Lead Data Scientist is the Co-Chair of PAW for Financial.
She provides advanced analytics consulting services including developing full life cycle predictive modeling processes from raw data exploration to model implementation into IT data systems, thorough documentation, and related training. Mei has over 14 years hands-on advanced analytics and machine learning experience dealing with large and complex data sets in various types of predictive analytics settings (claims, underwriting, pricing). She also has extensive traditional actuarial analysis experience including pricing, reserving, and research & development in the insurance industry. She has presented at many conferences to share and discuss her papers and expertise in predictive analytics with industry analytics experts.
Mei holds a Bachelor of Science in Actuarial Science from Hunan University and two Master of Science degrees, in Applied Mathematics and in Statistics, from Washington State University. Mei is a member of the American Statistical Association and a Certified Specialist in Predictive Analytics (CSPA) of the Casualty Actuarial Society.
Director, Senior Trading Strategist
George Papaioannou, is a Senior Trading Strategist within the Scientific Implementation Group of Bank of America Merrill Lynch. A Global quantitative team employing systematic, quantitative and scientifically informed methodologies around execution, portfolio management, and risk management, with emphasis on development of client solutions. George joined BAML in May 2018, following 12 years in energy major Shell, where he worked on a variety of functions. His latest role was in a team of computational science specialists, advising on machine learning, data, cloud, and high performance computing projects. He has previously worked in production operations, oil and gas forecasting, production optimization, reservoir management, development and project execution, for offshore fields in Brunei. The first 5 years of his industry career he worked in R&D as a scientific software developer focusing on scalable solvers and high performance computing. George holds a PhD in Computational Fluid Mechanics from the Massachusetts Institute of Technology, where he also completed two MSc degrees and worked as a post-doctoral associate for a year. He has authored academic articles and acted as referee for several scientific journals.
George Papaioannou is speaking in 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 speaking in the following session:
Head of Technology Innovation
Viktoriia Samatova is a Director of Applied Innovation team of Data Scientists within Reuters Technology division focused on discovering and applying new technologies to enhance Reuters products and improving efficiency of news content production and discoverability. Prior to joining Reuters, Viktoriia spent over 5 years at State Street Bank’s Global Exchange division where she was managing product development of academic and financial industry content ingestion platform, which was the first company-wide product application utilizing emerging technologies of AI and machine learning.
Viktoriia Samatova is speaking in the following session:
Finance & Analytics Leader
Finance & Analytics leader with over 20 years of experience producing measurable top line and bottom line results. Led a team responsible for financial planning and analysis, budgeting, and forecasting for $1.7 Billion in revenue for Paychex's largest divisions spanning 80+ locations in the United States and Germany. Also currently leading data science and predictive analytics.
Shadi Sifain is speaking in the following session:
Head Of Analytics
With over 20 years of professional expertise, Harphajan has led global business transformations across Wealth Management, Insurance, Retail and Institution Asset Management as well as Corporate Business Strategy in a diverse set of markets
Harphajan Singh is speaking in the following session:
Head of Data and Analytics
Tarun Sood is head of data and analytics in Vanguard Institutional Investor Group. He leads four different teams; Data Management and Governance: Business Intelligence and Reporting; Data Science and AI; Data and ML Engineering. The main goal of his group is to deliver actionable insights to the business in a timely manner. Prior to Joining Vanguard, Tarun worked as a strategy and analytics leader in a consulting capacity for over 15 years. He has implemented various solutions: Big Data & predictive Analytics, Advanced visualizations & Business Intelligence, Data Lakes both on premise and on cloud, Internet of Things (IoT), Enterprise Data Warehousing, Enterprise Data Governance, and multi domain Master Data Management. He has a track record of establishing and maintaining successful partnerships with Business and IT executives. He has successfully led large global teams with multi-million dollar portfolios across the Americas and Asia with a proven record of accomplishments.
Tarun Sood is speaking in 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 speaking in the following session:
David Stephenson Ph.D.
Author and Founder
David Stephenson is a data strategy consultant, trainer and part-time faculty at the University of Amsterdam Business School. He has assisted many small and large companies (adidas, IKEA, ABN Amro, Axel Springer, Miro, etc.) in establishing and developing their internal data science programs.
David was previously Head of Global Business Analytics for eBay Classifieds Group, where he worked with teams of data scientists and data engineers spread across six continents. He is the author of Big Data Demystified, a best selling guide for nontechnical executives, as well as the forthcoming Business Skill for Data Scientists, which encapsulates core principles from training programs he has developed. David earned his PhD at Cornell University and is now based in Amsterdam.
David Stephenson Ph.D. is speaking in the following session:
Edo van Uiter
Senior Data Scientist/Team Lead
Edo van Uitert started working for ABN AMRO in 2018 as data scientist for the Non-Financial Risk grid, where he worked on a variety of topics, including a text mining analysis of customer complaints and a predictive model for credit fraud. In August 2019 he moved to the Detecting Financial Crime Data Science Innovation team, where he develops novel advanced analytics methods to improve transaction monitoring. In 2012 Edo obtained his PhD in astronomy from Leiden University on the topic of weak gravitational lensing. After six years of research at the University of Bonn and University College London, he decided to change careers and transitioned into data science.
Edo van Uiter is speaking in the following session:
Lead Data Scientist
Min Yu is a Lead Data Scientist at Axis Capital. She specializes in AI transformation of the insurance business including personal, commercial, and specialty lines by developing and deploying machine learning models within the business process. Min holds a Ph.D. in Physics from the University of Illinois at Urbana-Champaign.
Min Yu is speaking in the following session: