
Technical Product Analyst - AI Model Ecosystem
Capgemini · New York, NY
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- On site
- Internship
- $102,000 / year
- New York, NY
Job highlights
- Lead AI model ecosystem vision and roadmap.
- Translate business needs into technical specifications.
- Utilize SQL, Python, and AI coding agents.
- Collaborate with engineering, risk, and data science.
- Ensure AI components meet risk controls.
About the role
Technical Product Analyst - AI Model Ecosystem
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
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).
Compensation and Benefits
The base compensation range for this role in New York, NY is $87,392 - $102,786. Capgemini provides comprehensive benefits including paid time off, medical, dental, vision, retirement savings plans, and life/disability insurance.
Key skills/competency
- Technical Product Analyst
- AI Model Ecosystem
- Model Risk Management
- SQL
- Python
- APIs
- Data Models
- System Architecture
- Product Requirements
- AI Coding Agents
Skills & topics
- Technical Product Analyst
- AI Model Ecosystem
- Model Risk Management
- SQL
- Python
- APIs
- Data Models
- System Architecture
- Product Requirements
- AI Coding Agents
- Product Owner
- Techno-Functional Business Analyst
- Analytics
- Geneartive AI
- LLM
How to get hired
- Tailor your resume: Highlight experience with AI, MRM, SQL, Python, and AI coding agents like Copilot.
- Showcase technical skills: Emphasize your ability to translate complex business needs into detailed product requirements and user stories.
- Demonstrate collaboration: Provide examples of working effectively with engineering, data science, and risk teams.
- Prepare for interviews: Be ready to discuss your understanding of model lifecycle, validation, and regulatory expectations, and your experience with AI coding agents.
- Research Capgemini: Understand their commitment to technology, sustainability, and inclusion to align your application.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific AI coding agents are required for the Technical Product Analyst role at Capgemini?
- The job description explicitly states that hands-on experience with AI coding agents such as GitHub Copilot, AMP, and Claude Code is mandatory for the Technical Product Analyst - AI Model Ecosystem position at Capgemini.
- What is the compensation range for the Technical Product Analyst at Capgemini in New York?
- The base compensation range for this Technical Product Analyst role in New York, NY is $87,392 to $102,786 annually. Actual compensation may vary based on experience, qualifications, and other factors.
- Does Capgemini offer remote work options for the Technical Product Analyst position?
- The Technical Product Analyst - AI Model Ecosystem position in New York, NY is listed as Onsite/Hybrid, indicating a combination of on-site and remote work flexibility is available.
- What level of experience is expected for a Technical Product Analyst at Capgemini focusing on AI?
- Capgemini looks for experience as a Technical Product Analyst, Product Owner, or Techno-Functional Business Analyst within AI, analytics, or model risk domains. Proficiency in SQL and Python, along with experience in APIs and data models, is crucial.
- How does Capgemini approach AI governance and model risk management in this role?
- This role is centered on AI-driven model ecosystems and Model Risk Management (MRM). You will be responsible for ensuring AI-enabled components align with model risk controls, interpretability standards, and governance frameworks, translating regulatory requirements into system capabilities.
- What are the primary programming languages and tools I'll use as a Technical Product Analyst at Capgemini?
- You will need strong proficiency in SQL and Python for data analysis and supporting feature design. Additionally, mandatory experience with AI coding agents like GitHub Copilot, AMP, and Claude Code is required.
- Can you describe the collaboration aspect of the Technical Product Analyst role at Capgemini?
- The role requires excellent collaboration skills with engineering, risk, and data science teams. You will partner with engineering to define data models and architecture, and collaborate with MRM, data science, engineers, and operations.