Data Scientist – Risk Analytics & AI Strategy Lead

Federal Reserve System•New York, NY

5d•$200,000 - $230,000•Onsite

About The Position

The Risk Analytics & Reporting Function drives data analytics and AI-augmentation product development to improve risk management decisions across FRBNY and System stakeholders. You'll serve as a strategic thought leader and central orchestrator for the Risk Function's analytics & AI portfolio, managing use case identification & refinement, data mining & modeling, and solution prototyping using machine learning & data analytics platforms. As the lead liaison to the FRBNY AI Governance Council and the System Risk AI Community of Practice, you'll balance innovation with strategic fit, ensuring each use case advances the broader AI integration roadmap while maintaining appropriate governance and fostering knowledge sharing across the Federal Reserve System.

Requirements

Hands-on coding proficiency in Python (PyTorch, TensorFlow), R, and SQL with experience in advanced techniques including time-series analysis, network analysis, NLP, and RAG
Understanding of Agentic AI concepts and expertise in crafting effective prompts for Large Language Models (LLMs)
Understanding of operational risk, credit risk, and enterprise-wide control frameworks within large-scale financial or regulatory environments
Demonstrated ability to streamline complex business processes and reduce operational spend through data-driven analysis with measurable results
Exceptional communication skills to translate complex technical concepts across audiences from technical teams to executives
Ability to build networks and influence stakeholders across various departments without direct authority

Responsibilities

Manage intake, prioritization, and refinement of data analytics & AI use cases while conducting structured workshops to identify opportunities, ensuring alignment with FRBNY and System-wide AI strategy.
Collaborate with data engineers to design, develop, and deploy advanced statistical and machine learning models for risk prediction and anomaly detection, while identifying and engineering Key Risk Indicators from diverse data sets.
Leverage internal tools to build prototype solutions for prioritized use cases while leading proof-of-concept development for selected high-priority AI applications.
Serve as the lead liaison to the System Risk AI CoP, ensuring internal risk requirements are prioritized in system-wide AI initiatives while fostering knowledge sharing across the Federal Reserve System.
Produce materials that facilitate socialization of AI initiatives for various stakeholders while fostering an environment of innovation within the Risk Function by encouraging exploration of technologies to automate manual risk functions.