T. Rowe Price
About the Team
Are you a curious problem solver who asks great questions and loves collaborating across disciplines?At T. Rowe Price, Data Scientists build the analytics and AI that power better investment decisions. Position is available in our New York City office or at our brand-new AI Data Science squad at our new Baltimore, MD Harbor Point location. Both locations offer the opportunity to collaborate with top talent, drive innovation, and make a real impact in asset management. If you’re a hands‑on leader who cares about people as much as technology, we’d love to talk.
Role Summary
This is a hands‑on, end‑to‑end lead role—from discovery to production. As a team leader, you will think creatively and scale modern AI/Data Science practices on Databricks, set team standards, and drive collaborative delivery. 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.
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.
Help shape elements of the data/ML platform strategy and drive execution within your domain.
Balance strategic and pragmatic concerns; proactively surface risks and resolve issues.
Qualifications Required: BS/MS in a quantitative field (CS, Statistics, Applied Math, Engineering, Economics) or equivalent; 5+ years in data science/ML.
Experience with automated pipelines, testing for data/models, and model lifecycle management (registry, versioning, monitoring).
Solid understanding of cloud‑native architectures (AWS).
Excellent communication and collaboration skills; adept at asking incisive questions and aligning diverse stakeholders.
Preferred: 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.
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 (e.g., H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant work status
. FINRA Requirements FINRA licenses are not required and will not be supported for this role. Work Flexibility This role is eligible for hybrid work, with up to three days per week from home.
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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.
Help shape elements of the data/ML platform strategy and drive execution within your domain.
Balance strategic and pragmatic concerns; proactively surface risks and resolve issues.
Qualifications Required: BS/MS in a quantitative field (CS, Statistics, Applied Math, Engineering, Economics) or equivalent; 5+ years in data science/ML.
Experience with automated pipelines, testing for data/models, and model lifecycle management (registry, versioning, monitoring).
Solid understanding of cloud‑native architectures (AWS).
Excellent communication and collaboration skills; adept at asking incisive questions and aligning diverse stakeholders.
Preferred: 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.
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 (e.g., H1-B visa, F-1 visa (OPT), TN visa or any other non-immigrant work status
. FINRA Requirements FINRA licenses are not required and will not be supported for this role. Work Flexibility This role is eligible for hybrid work, with up to three days per week from home.
#J-18808-Ljbffr