At T. Rowe Price, Data Scientists build the analytics and AI that power better investment decisions. T. Rowe Labs is focused on building the firm’s next-generation data and AI platform, aiming to seamlessly deliver on-demand ML-powered insights across our firm.
Requirements
- Experience with automated pipelines, testing for data/models, and model lifecycle management (registry, versioning, monitoring).
- Solid understanding of cloud‑native architectures (AWS).
- Experience with AI/GenAI (LLMs, RAG, prompt design/evaluation).
- Strong Python and Spark expertise; hands‑on Databricks experience (Delta Lake, Unity Catalog, MLflow, Jobs/Workflows).
- Time‑series/NLP experience; BI/analytics tooling (Databricks SQL, Tableau/Power BI, dbt).
- A solid understanding of financial markets and instruments.
- Commitment to quality via unit/integration tests, data validation, documentation, and code review.
Responsibilities
- Contribute to the full data & model lifecycle: problem framing, EDA, feature engineering, modeling, evaluation, deployment, and monitoring.
- Develop production solutions in Python (pandas, PySpark) on Databricks (Delta Lake, Unity Catalog, MLflow, Workflows/Jobs); apply CI/CD and reproducible experiments.
- Employ automated testing for code, data, and models (unit tests, data validation, drift/bias checks); ensure repeatable pipelines.
- Identify and address data/model technical debt; improve schemas, data contracts, and performance/cost.
- Deliver well-defined work items; clarify requirements through thoughtful questions and proposals.
- Mentor data scientists and engineers; lead code/design reviews and foster a collaborative culture.
- Own the quality, maintainability, security, governance, and total cost of ownership of delivered solutions.
Other
- As a team leader, you will think creatively and scale modern AI/Data Science practices on Databricks, set team standards, and drive collaborative delivery.
- Excellent communication and collaboration skills; adept at asking incisive questions and aligning diverse stakeholders.
- A solid understanding of financial markets and instruments.
- This role is eligible for hybrid work, with up to three days per week from home.
- Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States
