AI Product Analyst

The AI Product Analyst is responsible for translating business needs into AI-enabled product capabilities by combining strong product analysis, data interpretation, and hands-on use of modern AI tools.

This role partners closely with product, engineering, data science, and business stakeholders to define requirements, generate insights, and support delivery of intelligent, data-driven features.

A key expectation of this role is the ability to work closely with business teams in real-world contexts to deeply understand problems, rapidly iterate on solutions, and translate evolving needs into scalable product capabilities.

The individual must be comfortable operating in ambiguous environments, engaging directly with end users, and refining requirements continuously based on feedback and observed usage.

This includes rapidly prototyping ideas, leveraging AI tools to validate concepts, and bridging the gap between business intent and technical implementation.

The role also involves leveraging generative AI and enterprise AI platforms to accelerate requirement drafting, scenario analysis, and decision-making.

Responsibilities include developing user stories, defining acceptance criteria, validating AI outputs, supporting testing of AI-driven features, and ensuring alignment with responsible AI practices and enterprise standards.

Strong experience in product or business analysis with ability to translate requirements into user stories and acceptance criteria

Ability to work directly with business stakeholders to understand problems, iterate quickly, and refine solutions based on feedback

Comfortable operating in ambiguous, fast-evolving environments with minimal upfront definition

Hands-on experience with AI tools such as ChatGPT, Claude, Gemini, Microsoft Copilot, and GitHub Copilot

Proficiency in prompt engineering and AI-assisted workflows (requirements, analysis, documentation)Strong analytical and problem-solving skills with a data-driven mindset

Experience working in Agile/SAFe environments with backlog management and sprint execution

Ability to validate AI outputs for accuracy, completeness, and business relevance

Strong collaboration skills across product, engineering, and data science teams

Understanding of APIs, data flows, and system interactions

Knowledge of Responsible AI principles

Experience working in high-touch, iterative delivery environments with close business engagement

Experience on AI/ML-enabled products or platforms

Familiarity with LLM-based systems, AI agents, or AI platforms

Experience using AI for: Requirement generation, Scenario modeling, Test case creation, Rapid prototyping of workflows

Basic knowledge of data analysis tools, SQL, or data modeling

Exposure to healthcare, insurance, or regulated domains

Experience with tools such as Jira, Confluence, or similar