Technical Product Analyst - AI Model Ecosystem

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Job Location : New York, NY (Onsite/Hybrid)

Job Description

We are seeking a Technical Business Analyst to lead the vision and roadmap for an AI‑Driven Model Ecosystem. This role operates at the intersection of AI product strategy and Model Risk Management (MRM), driving end‑to‑end design, requirements, and delivery of AI‑enabled model governance capabilities. The ideal candidate excels at translating complex business needs into technical specifications, designing intelligent workflows, and enabling model lifecycle processes through modern AI, automation, and data engineering practices.
Experience with AI coding agents (GitHub Copilot, AMP, Claude Code) is mandatory.

Required Skills Qualifications

• Experience as a Technical Product Analyst, Product Owner, or Techno‑Functional Business Analyst in AI, analytics, or model risk domains.
• Strong proficiency in SQL and Python.
• Experience working with APIs, data models, and system architecture fundamentals.
• Proven ability to turn ambiguous challenges into structured analytical problem statements.
• Strong capability in writing product requirements, user stories, and acceptance criteria.
• Excellent collaboration skills with engineering, risk, and data science teams.
• Deep understanding of Model Risk Management (MRM), model lifecycle, validation, monitoring, and regulatory expectations.
• Outstanding communication skills and ability to simplify complex concepts.
• Mandatory: Hands‑on experience using AI coding agents such as GitHub Copilot, AMP, and Claude Code.

Key Responsibilities

• Own the product vision, roadmap, and feature evolution for an AI‑driven model ecosystem.
• Analyze data using SQL and Python to support feature design, validation logic, and lifecycle workflows.
• Interpret complex model governance, validation, and regulatory requirements and translate them into system capabilities.
• Break down ambiguous problems into structured analysis, hypotheses, and actionable product work.
• Translate business and user needs into detailed product requirements, functional specs, and user stories.
• Design workflows and user journeys supporting model development, validation, approval, monitoring, and retirement.
• Partner with engineering teams to define data models, APIs, integrations, and architecture for model governance platforms.
• Collaborate with cross‑functional groups including MRM, data science, engineers, and operations.
• Support UAT planning, test case design, execution, and defect resolution.
• Ensure all AI‑enabled components align with model risk controls, interpretability standards, and governance frameworks.
• Use AI coding agents (Copilot, AMP, Claude Code) to enhance analysis, documentation, workflow design, and solution delivery.
• Stay current with innovations in AI model governance, workflow automation, and risk oversight.

Good to Have

• Experience with model inventory or model governance platforms.
• Familiarity with AI workflows, RAG architectures, vector databases, and LLM‑driven automation.
• Understanding of AI governance, model explainability, and interpretability frameworks.
• Experience with workflow orchestration or AI orchestration tools (e.g., LangChain, Semantic Kernel).

The base compensation range for this role in the posted location is: 87392-102786

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may