AI Product Data Analyst

Join HiBob, a rapidly growing HR platform that helps modern businesses manage their people effectively. As an AI Product Data Analyst, you will play a crucial role in bridging user behavior and model performance, defining KPIs, and driving feature adoption. You will need at least 3 years of experience in product data analytics, advanced SQL skills, and hands-on experience with LLM concepts. Strong communication and critical thinking skills are essential.

Responsibilities

• Defining KPIs, building the semantic layer for Product Agents, and iterating on AI outputs.
• Analyzing large-scale product usage datasets and providing insights that directly impact strategy and feature adoption.
• Collaborating with cross-functional teams to translate complex data and AI concepts into clear, strategic narratives.

Requirements

• 3+ years of experience in product data analytics, preferably within a B2B SaaS environment.
• Advanced SQL skills and experience analyzing large-scale product usage datasets.
• Hands-on experience with LLM concepts, including basic prompt engineering, output evaluation, or experimenting with GenAI tools.
• Proven track record with BI & data visualization tools (e.g., Tableau, Streamlit) to build executive-ready dashboards.
• Strong foundation in data modeling, semantic layers, and event tracking design (defining schemas, user journeys, and funnel metrics).
• Critical Thinking in Ambiguity: Ability to challenge assumptions, identify patterns in noisy AI outputs, and turn imperfect data into sound recommendations.
• Product & Business Acumen: A strong drive to connect data insights directly to user needs, product opportunities, and bottom-line business impact.
• Ownership & Proactivity: A self-starter mentality with the ability to navigate ambiguity, ask the right questions, and drive complex analyses through to action.
• Communication & Influence: Excellent ability to translate complex data and AI concepts into clear, strategic narratives that align and influence cross-functional stakeholders.

Preferred

• Practical experience with dbt, Git, and data transformation workflows.
• Familiarity with MCP (Model Context Protocol), database agents, or semantic views.
• Experience using AI-assisted development tools (e.g., Cursor, Claude Code, GitHub Copilot) to accelerate coding and analytical speed.
• Exposure to advanced LLM workflows, fine-tuning, or structured evaluation frameworks.