HiBob helps modern, mid-size businesses transform the way they manage people, giving HR and managers all they need to connect, engage, develop, and retain top talent. Since 2015, we’ve achieved consecutive triple-digit year-over-year growth, all backed by our amazing team of Bobbers from across the globe, making us the choice HRIS of over 5,500 midsize and multinational companies and over 1 Million users.
Our HR platform is intuitive, data-driven, and built for the way people work today: globally, remotely, and collaboratively.
As part of this evolution, HiBob is investing in building an AI-first platform. The AI Unit is responsible for developing the AI layer that powers intelligence across the product, from user-facing experiences to the underlying capabilities and systems that enable them.

About the Role
We are looking for a highly analytical AI Product Analyst to join our core Product Analytics tech team. Operating at the intersection of data, Product and Tech, you will be the bridge between user behavior and model performance. You will partner with Product and Tech leadership to define KPIs, build the semantic layer for Product Agents, and iterate on AI outputs. Your insights will directly impact our strategy, drive feature adoption, shape our data infrastructure, and deliver measurable business impact.

• 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).

Core Competencies & Mindset

• 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.

Nice to Have

• 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.

• Empower Strategic Decisions: Translate complex usage data into executive-ready dashboards and actionable recommendations that align cross-functional stakeholders.
• Enable AI Data Infrastructure: Build and maintain the semantic layer for Product Agents to unlock intelligent, self-serve data discovery across the organization.
• Drive Product Growth: Analyze the user journey to proactively identify adoption gaps and friction points, accelerating feature activation, retention, and growth.
• Optimize AI & Feature Impact: Measure roadmap launches and iterate on prompt engineering and model evaluation to continuously elevate AI performance and user experience.
• Standardize Metrics & Tracking: Partner with Product leadership to define core KPIs, unify metric definitions, and establish robust event tracking.
• Accelerate Delivery Velocity: Leverage AI-assisted development tools (e.g., Cursor, Claude Code) to streamline technical workflows and increase analytical output speed.