AI Data Scientist (NYC)

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.

About This Position

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. We’re seeking an AI Data Scientist to join our Union Square, NYC office, partnering with business and technology teams to transform complex questions into reliable, explainable outcomes. If you enjoy hands-on work and tackling challenging problems with technology, we want to connect with you.

Role Summary

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.

Responsibilities

• 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.

Qualifications

Required:

• 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.

Preferred:

• 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 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.