AI Data Scientist

At T. Rowe Price, we identify and actively invest in opportunities to help people thrive in an evolving world. As a premier global asset management organization with more than 85 years of experience, we provide investment solutions and a broad range of equity, fixed income, and multi-asset capabilities to individuals, advisors, institutions, and retirement plan sponsors. We take an active, independent approach to investing, offering our dynamic perspective and meaningful partnership so our clients can feel more confident.

We believe doing the right thing for our clients and our associates is good business. With a career at the firm, you can expect opportunities to create real impact at work and in your community. You’ll enjoy resources to support your career path, as well as compensation, benefits, and flexibility to enrich your life. Here, you’ll find a collaborative culture that respects and values differences and colleagues who share a spirit of generosity.

Join us for the opportunity to grow and make a difference in ways that matter to you.

Are you a collaborative problem solver who thrives on asking insightful questions and working across disciplines? At T. Rowe Price, our Data Scientists develop the analytics and AI solutions that drive 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 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 enjoy hands‑on work and tackling challenging problems with technology, we want to connect with you.

This is a hands‑on role covering the entire data science workflow, from discovery through production deployment. You’ll creatively apply modern AI and data science techniques on Databricks, working closely with business partners. As part of T. Rowe Labs, you’ll help build our next‑generation data and AI platform, delivering on‑demand, ML‑powered insights across the firm.

Engage in all phases of the data science lifecycle: problem framing, exploratory data analysis, feature engineering, modeling, evaluation, deployment, and monitoring, with guidance from senior team members.

Develop robust Python notebooks, jobs, and pipelines (using pandas, scikit‑learn, PySpark) on Databricks (Delta Lake, Unity Catalog, MLflow, Jobs/Workflows).

Implement testing and quality checks, including unit tests, data validation, and drift/bias monitoring; maintain reproducible experiments and clear documentation.

Participate in code and design reviews, use git and CI/CD, and manage technical debt.

Clarify requirements, propose iterative solutions, and communicate findings to both technical and non‑technical stakeholders.

Collaborate with platform and governance teams to ensure security, lineage, and auditability.

• BS/MS in a quantitative field or equivalent experience; 2+ years in data science or machine learning.
• Solid understanding of experimental design, model validation, metrics, and foundational MLOps concepts.
• Strong collaboration and communication skills, with a question‑first approach; comfortable partnering directly with business stakeholders.
• Familiarity with AWS basics and git/CI workflows.

• Experience with AI/Generative AI (LLMs, RAG, prompt engineering/evaluation).
• Advanced Python skills for data science (pandas, scikit‑learn); experience with PySpark.
• Hands‑on experience with Databricks (Delta Lake, MLflow, Jobs/Workflows) or equivalent Spark platforms, with a desire to expand expertise.
• Knowledge of time‑series analysis or NLP; experience with BI/analytics tools (Databricks SQL, Tableau/Power BI, dbt).
• Familiarity with financial markets and instruments.

FINRA licenses are not required and will not be supported for this role.

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…