Donald Dinerman
Senior Associate, Data Science @ JPMorganChase
About
Data Scientist at JPMorganChase building and maintaining automated forecasting platforms on large-scale transactional and behavioral data. My work focuses on developing, deploying, and monitoring forecasting and predictive models that support high-stakes financial and operational decisions. I primarily work in Python and SQL, with an emphasis on time series modeling, feature engineering, and scalable automation. I hold a Master’s in Statistical Practice from Carnegie Mellon, with a background in Economics, Statistics, and Behavioral Economics.
United States
New York
Banking
Linux, Python (Programming Language), R (Programming Language), Machine Learning, Google Analytics, MySQL, LaTeX, Git, English, Portuguese
Experience
Senior Associate, Data Science
JPMorganChase
New York, New York, United States
- Built and maintained an automated forecasting platform supporting 200+ monthly sales and budget forecasts - Developed Python-based time series models informing pricing and media budget allocation - Integrated external loyalty and transactional data into production forecasting pipelines - Designed scalable workflows to automate model execution and monitoring
Associate, Data Science
JPMorganChase
New York, New York, United States
- Built predictive and geospatial models to support Auto repossession operations using Python, PySpark, and SQL - Created data-driven frameworks to inform branch staffing and headcount timing across 250+ planned locations - Optimized large-scale pipelines processing millions of card transactions
CMU-Optum Summer Researcher
Optum
Pittsburgh, Pennsylvania, United States
- Performed comprehensive data exploration and applied K-means++ clustering on US maternal health care data to identify high-risk pregnancies - Built a generalized additive model to predict premature deaths using county-level health behavior data
Teaching Assistant, 36-315: Statistical Graphics & Visualization
Carnegie Mellon University
Pittsburgh, Pennsylvania, United States
- Worked closely with TAs and professors to grade assignments/exam material and hold recitations for 100+ students - Topics include Linear/Logistic Regression, Hierarchical Clustering, KNN, PCA, etc
Operations Analyst
BNY
Pittsburgh, Pennsylvania, United States
- Input 100s of manual trade instructions working with the Pittsburgh Instruction Processing Group - Analyzed processing data to estimate the impact of a new OCR-based data entry initiative on workforce productivity
Research and Data Analytics
Makin Wellness
Pittsburgh, Pennsylvania, United States
- Used Google Analytics to inform semantic and technical website edits to improve search engine optimization
Education
Carnegie Mellon University
Statistical Practice
Carnegie Mellon University
Economics and Statistics
Carnegie Mellon University
Behavioral Economics, Policy and Organizations
Donald Dinerman's Contact Information
Phone
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