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.
Job responsibilities
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.
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).
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.
This position is open to all candidates.