About the Role
As a Senior Manager / Principal Data Scientist, you will innovate and improve the machine learning models we rely on to make billions of dollars of efficient and accurate decisions and to enable financial progress for our customers.
Responsibilities
- Design, develop, and deploy machine learning models to solve practical problems and help our business and customers reach their financial goals.
- Partner with business leaders and technical experts across the company to develop new data sources, improve our modeling methodology, and apply models with sound risk management.
Requirements
- Has created, deployed, and managed supervised learning models in production systems for vital applications and enjoys being a technical mentor.
- Has a PhD in a quantitative field and 3+ years of experience in a related role or a BS / MS in a quantitative field and 7+ years of experience in a related role.
- Shares best practices for software engineering and can help smart, experienced data scientists with complex technical problems - especially operationalizing and evaluating models for real-world applications.
- Considers themself a generalist data scientist more motivated by practical solutions than theoretical elegance.
- Practices solid fundamentals with software engineering (test-driven development, code review, refactoring) and the PyData stack (numpy, scikit-learn, pandas, etc.).
- Is interested in a wide range of ML solutions, including established tools (e.g. Spark, Kubernetes, Airflow, MLFlow), emerging tools (like Chalk, BentoML, or DVC), and developing in-house tools.
Bonus Points For
- Experience managing a strong technical team.
- Experience building predictive models end to end.
- Experience solving problems in consumer lending or fintech.
- Interest in developing ways to train, interpret, and deploy neural network architectures for time series classification tasks.