Zach Elewitz Director of Data Science

Director of Data Science

WEX

Jan 2022 - Current (4 years 8 months)

Responsible for delivering artificial intelligence and data science products for every line of business. Transformed a small R&D group into delivery-focused artificial intelligence and data science teams. These teams now produce robust, high-quality, auditable models that make a $5M+ impact annually. Major accomplishments include: Leading the Artifical Intelligence and Data Science Teams • Founded the AI team and facilitated the development and utilization of AI across the organization • Establishing MLOps for deploying, monitoring, and maintaining batch and real-time models including large language models, deep reinforcement learning, and the foundational machine learning models • Lead the end-to-end planning and execution of all data

Manager of Data Science

Neiman Marcus

Jan 2021 - Jan 2022 (1 year 1 month)

Led three data science teams focused on quantifying customer lifetime value and market segmentation. This empowered the luxury retailer to tailor their customer outreach, crucial in adapting to the post-COVID landscape, designed to increase customer spending behavior. Major accomplishments include: • Led the strategic development of the data science program (managed three teams of 15+ data scientists) • Predicted customer lifetime spend via demographic information and transaction history • Developed a customer churn model that identified customers needing retentive actions • Designed multivariate A/B testing preceding the full roll out of new data science solutions • Created data science driven customer segments that empowered customer

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pythia

Aug 2020 - Current (6 years 1 month)

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Head of Analytics & Data Science

Jan 2020 - Jan 2022 (2 years 1 month)

Responsible for the development and deployment of the cryptocurrency trading engine built to identify opportunities for value-based trading and arbitrage. This consisted of building the tech stack from scratch, balancing features for revenue generation versus code stability, and data governance. Major accomplishments include: • Hands-on coding of the trading engine, ETL pipelines for data capture/cleaning, and back-testing validation • Directed the software engineering team in the development of new features, POCs, and integration testing • Implemented governance that ensured standardized definitions, peak data quality, and hygienic data practices • Developed new trading strategies, tested proofs of concept, and deployed new features

Project Lead/Senior Machine Learning Engineer

Pearson

Jan 2018 - Jan 2020 (2 years 1 month)

• Led a team of 4 in • Automating the process of identifying math skills and their prerequisite relationships within a textbook • Creating a student simulator demonstrating that the skill prerequisite relationships supports adaptive testing • Drive machine learning products from ideation to performant, extensible, cost-efective solutions • Deployed a test grade predictor that advises teachers on which students will struggle with upcoming exams and recommends intervening actions so that they can proactively prevent grades from dropping before it even occurs

Senior Data Scientist

Ernst & Young

Jan 2014 - Jan 2017 (3 years 1 month)

• Pitched and sold machine learning solutions to multinational financial institutions • Invented an anomaly detection technique for real-time intruder detection that increased identification by 130% • Built a loan delinquency predictor (neural network) that increased prediction accuracy by 53% • Created an interactive dashboard for identifying cost flows and critical resources to justify solvent wind-down plans to the U.S. government, saving over 5,000 man-hours annually • Formulated the legal entity rationalization strategy for numerous multi-billion dollar institutions in order to prepare for instances of material financial distress and to pose minimal risk to U.S. financial stability

Zach Elewitz

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