Director, Data Science Job

Build and deploy machine learning and statistical models to support business needs, particularly in credit risk assessment, pricing, fraud detection, and loss forecasting. Analyze large datasets using tools such as Python and SQL to support data-driven decision-making. Evaluate internal and external data sources to support feature development and collaborate with data engineering and analytics teams to build scalable feature engineering processes. Stay up to date with the latest trends and technologies in data science and fintech, actively researching and evaluating new tools and techniques for model development. Collaborate cross-functionally with risk, product, and engineering teams to develop and implement data-driven strategies.

*May telecommute from any location in the United States.

Minimum Requirements:

Education: Master’s degree in Data Science, Statistics, or in a related field.

Experience: Seven (7) years of experience in the job offered or as a Machine Learning Scientist or in a related occupation..

Skills: Experience in applying statistical and machine learning techniques to build predictive models on structured or financial datasets; Python and SQL for data manipulation, analysis, and model development; applying quantitative methods to credit risk or financial datasets to conduct analyses such as portfolio segmentation, or reject inference, or similar analytical approaches; cloud computing platforms to support data analysis and machine learning workflows; implementing predictive models into production or operational environments; applying model explainability techniques to interpret predictive models and communicate insights for business or customer-facing decisions; and credit risk practices across the credit lifecycle, including underwriting, pricing, and account management.

APPLY TO: Upgrade, Inc.
Reference Job #146
275 Battery Street, Suite 2300
San Francisco, CA 94111