Risk Data Analytics Product Owner & Reporting Lead

Federal Reserve Bank of Philadelphia•New York, NY

11d•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. This role serves as the analytical translator and product architect for risk profile visualization and reporting capabilities. The ideal candidate is a "data whisperer" who excels at taking initial hypotheses or business questions and transforming them into rigorous analytical problems, then seeing those problems through from initial concept to final executive presentation. This role combines analytical translation skills, technical depth in data modeling and visualization, product ownership mindset, and executive communication capabilities to enable Risk, business, and executive stakeholders to monitor vulnerabilities, identify emerging trends, and make data-informed decisions. The role encompasses the full analytical lifecycle: partnering with stakeholders to frame questions, defining data requirements, conducting exploratory data analysis, engineering features, creating visualizations, and crafting compelling narratives that translate complex findings into actionable business insights. This position works closely with risk professionals across the Federal Reserve System (FRS) to understand ambiguous business challenges, translates these into concrete analytical approaches, executes the analysis, and communicates findings through both self-service tools and targeted dashboards.

Requirements

Analytical translation skills
Technical depth in data modeling and visualization
Product ownership mindset
Executive communication capabilities
Ability to monitor vulnerabilities, identify emerging trends, and make data-informed decisions
Ability to frame questions, define data requirements, conduct exploratory data analysis, engineer features, create visualizations, and craft compelling narratives
Experience working closely with risk professionals across the Federal Reserve System (FRS) to understand ambiguous business challenges, translate these into concrete analytical approaches, execute the analysis, and communicate findings through both self-service tools and targeted dashboards.
Experience partnering with business stakeholders to translate initial hypotheses, questions, or ambiguous problems into structured analytical frameworks and data analysis approaches.
Experience leading discovery sessions with risk professionals and subject matter experts to frame the "question behind the question” and probe beyond initial requests to uncover the underlying business need and ensure analyses address root issues rather than surface symptoms.
Hands-on experience with data sets and visualization tools (e.g., Tableau, Power BI, Python, R) to perform exploratory analysis, feature engineering and data modeling to test hypotheses and communicate findings.
Experience employing data visualization best practices and advanced analytics techniques to transform complex risk data into intuitive, actionable insights for various risk audiences (management, risk officers).
Experience establishing repeatable processes and templates for common risk analytics use cases to enable self-service reporting capabilities.
Experience conducting regular user feedback sessions, usability studies, and user acceptance testing to ensure visualization and reporting products meet the evolving needs of risk management workflows.
Experience designing and developing business-driven analytics products including interactive dashboards, risk profile reports, and KRI monitoring solutions that leverage structured and unstructured data from enterprise data infrastructure.
Experience building strong partnerships with risk professionals, business stakeholders, and subject matter experts across the FRS to understand risk reporting personas, workflows, pain points, visualization needs, and KRI requirements.
Experience leading the operationalization of Key Risk Indicators (KRIs), including developing business logic and data sourcing requirements, implementing automated monitoring workflows, and integrating KRIs into the broader risk profile visualization and reporting interfaces.
Experience leading the discovery, capture and refinement of AI use cases that can enhance risk profile visualization and reporting, and drive both experimentation and path to production in partnership with data scientists and TG resources.
Experience contributing to the shaping of a Risk Data Strategy and driving the implementation of the strategy through data sourcing and modeling requirements that support analytics and reporting products.
U.S. citizens, lawful permanent residents, individuals who meet the definition of “protected individual” under 8 U.S.C. § 1324b(a)(3), and certain other nonimmigrants. All non-U.S. citizens authorized to access CSI and/or FOMC information must sign a declaration of intent to expeditiously become a lawful permanent resident and thereafter a U.S. citizen when eligible.

Nice To Haves

AI-augmentation product development
Machine learning & data analytics platforms
Experience with the FRBNY AI Governance Council
Experience with the System Risk AI Community of Practice
Experience with AI integration roadmap
Experience with appropriate governance
Experience fostering knowledge sharing across the Federal Reserve System
Experience with data mining
Experience with solution prototyping
Experience with data modeling
Experience with visualization
Experience with product ownership
Experience with executive communication
Experience with risk profile visualization
Experience with reporting capabilities
Experience with risk management
Experience with data analytics
Experience with AI
Experience with risk management decisions
Experience with FRBNY
Experience with System stakeholders
Experience with analytics & AI portfolio
Experience with use case identification & refinement
Experience with data mining & modeling
Experience with machine learning & data analytics platforms
Experience with AI Governance Council
Experience with System Risk AI Community of Practice
Experience with AI integration roadmap
Experience with appropriate governance
Experience fostering knowledge sharing
Experience with Federal Reserve System
Experience with analytical translation skills
Experience with technical depth in data modeling and visualization
Experience with product ownership mindset
Experience with executive communication capabilities
Experience with risk, business, and executive stakeholders
Experience with monitoring vulnerabilities
Experience with identifying emerging trends
Experience with data-informed decisions
Experience with the full analytical lifecycle
Experience partnering with stakeholders to frame questions
Experience defining data requirements
Experience conducting exploratory data analysis
Experience engineering features
Experience creating visualizations
Experience crafting compelling narratives
Experience translating complex findings into actionable business insights
Experience working closely with risk professionals
Experience understanding ambiguous business challenges
Experience translating business challenges into concrete analytical approaches
Experience executing analysis
Experience communicating findings through both self-service tools and targeted dashboards
Experience with risk professionals across the Federal Reserve System (FRS)
Experience with ambiguous business challenges
Experience with concrete analytical approaches
Experience with analysis execution
Experience with self-service tools
Experience with targeted dashboards
Experience with data sets
Experience with visualization tools (e.g., Tableau, Power BI, Python, R)
Experience with exploratory analysis
Experience with feature engineering
Experience with data modeling
Experience with hypothesis testing
Experience with findings communication
Experience with data visualization best practices
Experience with advanced analytics techniques
Experience with complex risk data
Experience with intuitive, actionable insights
Experience with various risk audiences (management, risk officers)
Experience with repeatable processes
Experience with templates for common risk analytics use cases
Experience with self-service reporting capabilities
Experience with user feedback sessions
Experience with usability studies
Experience with user acceptance testing
Experience with visualization and reporting products
Experience with evolving needs of risk management workflows
Experience with business-driven analytics products
Experience with interactive dashboards
Experience with risk profile reports
Experience with KRI monitoring solutions
Experience with structured and unstructured data
Experience with enterprise data infrastructure
Experience building strong partnerships
Experience with risk professionals
Experience with business stakeholders
Experience with subject matter experts
Experience with the FRS
Experience with risk reporting personas
Experience with workflows
Experience with pain points
Experience with visualization needs
Experience with KRI requirements
Experience leading the operationalization of Key Risk Indicators (KRIs)
Experience developing business logic
Experience developing data sourcing requirements
Experience implementing automated monitoring workflows
Experience integrating KRIs into the broader risk profile visualization and reporting interfaces
Experience leading the discovery, capture and refinement of AI use cases
Experience enhancing risk profile visualization and reporting
Experience driving experimentation and path to production
Experience in partnership with data scientists and TG resources
Experience contributing to the shaping of a Risk Data Strategy
Experience driving the implementation of the strategy
Experience with data sourcing and modeling requirements
Experience supporting analytics and reporting products

Responsibilities

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.
Serve as the lead liaison to the FRBNY AI Governance Council and the System Risk AI Community of Practice, balancing 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.
Partner with business stakeholders to take initial hypotheses, questions, or ambiguous problems and translate them into structured analytical frameworks and data analysis approaches.
Lead discovery sessions with risk professionals and subject matter experts to frame the "question behind the question” and probe beyond initial requests to uncover the underlying business need and ensure analyses address root issues rather than surface symptoms.
Work hands-on with data sets and visualization tools (e.g., Tableau, Power BI, Python, R) to perform exploratory analysis, feature engineering and data modeling to test hypotheses and communicate findings.
Employ data visualization best practices and advanced analytics techniques to transform complex risk data into intuitive, actionable insights for various risk audiences (management, risk officers).
Establish repeatable processes and templates for common risk analytics use cases to enable self-service reporting capabilities.
Conduct regular user feedback sessions, usability studies, and user acceptance testing to ensure visualization and reporting products meet the evolving needs of risk management workflows.
Design and develop business-driven analytics products including interactive dashboards, risk profile reports, and KRI monitoring solutions that leverage structured and unstructured data from enterprise data infrastructure.
Build strong partnerships with risk professionals, business stakeholders, and subject matter experts across the FRS to understand risk reporting personas, workflows, pain points, visualization needs, and KRI requirements.
Lead the operationalization of Key Risk Indicators (KRIs), including developing business logic and data sourcing requirements, implementing automated monitoring workflows, and integrating KRIs into the broader risk profile visualization and reporting interfaces.
Lead the discovery, capture and refinement of AI use cases that can enhance risk profile visualization and reporting, and drive both experimentation and path to production in partnership with data scientists and TG resources.
Contribute to the shaping of a Risk Data Strategy and drive the implementation of the strategy through data sourcing and modeling requirements that support analytics and reporting products.