We have an opening for a Manager of Product Data & Analytics to lead, mentor, and empower a high-impact team of product analysts.

In this role, you and your team won't just report on what is happening in our product—you will help us understand why, and drive the strategic consensus on what we should do about it.

About The Role

Data can tell us that conversion fell. Your team’s job is to tell us why.

Did we impact the product experience? Did the acquisition mix change? Did we bring in lower-intent customers? Did pricing or an onboarding change alter behavior? Did instrumentation change? Is an aggregate metric hiding materially different results across channels, platforms, cohorts, or customer segments?

This is a leadership role for a battle-tested product problem solver who leads from the front. You will build a culture of analytical rigor and partner closely with leaders across Product, Design, Engineering, Growth, Marketing, and Finance to diagnose performance, evaluate launches, and shape our product roadmap.

Our data is accessible through Snowflake and modern AI tooling, including Claude Code. As a manager, you will elevate your team’s execution, ensuring they frame the right questions, interrogate data rigorously, recognize when the obvious answer is wrong, and turn evidence into clear, decisive recommendations.

What You'll Do

• Lead and Develop the Team: Build, coach, and mentor a high-performing team of product analysts. Foster an environment of high agency, intellectual curiosity, continuous learning, and career development. Set a high bar for analytical quality, business impact, and storytelling.
• Drive Strategic Product Decisions: Partner directly with Product, Engineering, and Business leaders to translate strategic questions into analytical agendas. Manage the analytics backlog, balance reactive requests with proactive deep-dives, and ensure the team is focused on high-leverage opportunities.
• Find the Mechanism, Not Just the Movement: Guide your team to investigate changes in activation, engagement, conversion, retention, and monetization until they understand the root drivers. Teach them to separate underlying product performance from shifts in acquisition volume, quality, mix, seasonality, and confounding factors.
• Instill Statistical & Methodological Rigor: Ensure the team accounts for Simpson's paradox, selection effects, survivorship bias, denominator changes, and instrumentation issues. Champion causal inference, rigorous experimental design (A/B testing), and proper statistical standards across all product evaluations.
• Build the Product Measurement Foundation: Oversee the definition and governance of trusted KPIs, leading indicators, metric trees, and customer segments. Work with Engineering and Product to establish telemetry and telemetry standards before products ship.
• Elevate Data Storytelling & Stakeholder Communication: Ensure complex analyses are translated into clean visuals, intuitive concepts, and actionable recommendations. Serve as a key voice in leadership discussions, including when the evidence challenges the prevailing narrative.
• Scale Analytical Leverage through AI: Drive the adoption of modern AI-native workflows (e.g., Claude Code, advanced SQL/Python, "vibecoding" metrics) across your team to multiply efficiency and automate repeatable work. Model a balanced approach: move fast, but aggressively validate code, logic, and output.

What We're Looking For

• Experience: 6+ years of experience in product analytics, growth analytics, or decision science, including 2+ years of direct people management or formal team leadership experience in a technology, subscription, SMB, or consumer-facing business.
• Leadership & Coaching: Demonstrated success in recruiting, mentoring, and retaining talent. A track record of leveling up junior/senior analysts in their statistical reasoning, product sense, and executive presence.
• Deep Product & Metric Fluency: Mastery of activation, engagement, conversion, retention, churn, monetization, and LTV mechanics—with the practical judgment to decompose complex metric movements into root causes.
• Applied Statistics & Experimentation: Strong foundation in experimentation, cohort analysis, hypothesis testing, sample sizing, and causal inference.
• Technical Mastery: High proficiency in SQL and cloud data warehouses (Snowflake, BigQuery, Databricks). Working knowledge of Python or R for statistical analysis.
• AI-Native Working Style: Enthusiasm for modern AI tools (Claude Code, ChatGPT, GitHub Copilot, Cursor) to multiply productivity, paired with the critical judgment to rigorously audit AI-generated code and assumptions.
• Product Intuition & Business Acumen: Exceptional product sense. You instinctively ask why users act a certain way and understand the downstream business and financial implications of user behavior.
• Communication & Influence: Excellent verbal, written, and visual communication skills. Comfortable pushing back on assumptions and presenting complex findings to VP and C-suite stakeholders.

Who You Are

• Experience with experimentation platforms (e.g., Statsig, Optimizely) and behavioral analytics platforms (e.g., Amplitude, Mixpanel, Google Analytics).
• Experience with growth/acquisition analytics, lifecycle marketing, or dbt/modern metric transformation layers.
• Educational background in Economics, Statistics, Computer Science, Mathematics, Psychology, or a related quantitative field.
• Experience in SMB tech, email/marketing technology platforms, or AI-powered product experiences.

What This Role Is Not

This is not a dashboard ticket-queue manager, a passive reporting function, or a pure people-admin role. Trusted KPIs and operational dashboards are essential foundations, but they are not the end goal.

The goal of this role is to build an elite analytics unit that serves as a core engine for better product understanding, higher-conviction product decisions, and measurable business growth.

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