Senior Data Scientist

5+ years of professional experience building and deploying machine learning models in a production environment Lending domain experience, applying data science principles in the management of portfolio risk or acquisition Bachelor’s or Master’s degree in a quantitative discipline (e.g., Computer Science, Statistics, Finance, Math, Engineering) Full stack data-science experience: ideating, building, deploying, monitoring, and maintaining production ML models that solve product needs and perform with high levels of accuracy, stability, and coverage The ability to communicate and present complex technical topics and results to various audiences Deep understanding of statistics, probability, and machine learning algorithms Strong software engineering and data engineering fundamentals Expert-level programming skills in Python and proficiency with core data science libraries (e.g., pandas, scikit-learn, Hugging Face) Excellent SQL skills and comfort working with large and complex data warehouses (Snowflake/Postgres) Experience with CI/CD, shell scripting, Git/version control, REST/GRPC APIs, and cloud infrastructure (AWS: S3, EKS, etc)

Partner with Product, Engineering, and other stakeholders to translate ambiguous business challenges into well-defined data science problems Own the end-to-end lifecycle of data science models, from data exploration and feature engineering to deployment, monitoring, and continuous improvement in production Develop robust, scalable, and efficient models, thoughtfully balancing algorithmic complexity against interpretability, business needs, and delivery timelines