Strategic Partnership: Work alongside cross functional teams to lead data initiatives that bridge Product, Engineering, and Marketing — making sure growth bets are measurable, correctly instrumented, and aligned with enterprise objectives.
Root Cause Investigation: Lead the deep-dive culture our team is known for. When metrics shift, you don't just report the drop-off; you investigate if it's a technical bug, a UX friction point, or a trust barrier. You turn these insights into a compelling narrative that shifts product strategy.
Architecting Analytical Frameworks: Design and standardize how we evaluate product growth and user behavior, turning ad-hoc investigation into a repeatable, high-signal process the whole team can run.
A/B Experimentation & Inference: Lead the experimentation lifecycle, from power analysis and hypothesis design to post-test causal inference and rollout. Leverage product analytics capabilities to understand how features impact user segments and behavior over time. Apply statistical methods to understand the long-term impact of product changes on user retention and Lifetime Value (LTV).
Financial Storytelling: Partner with FP&A to pressure-test growth forecasts and connect product outcomes to revenue, LTV, and segment-level P&L impact.
Raising the Analytical Bar: You lead by example and set a high standard for analytical excellence. Through your daily work, you model best practices in modern, AI-enhanced workflows and help elevate the broader team’s capability in high-signal data storytelling and statistical rigor.
End-to-End Project Ownership: Take full ownership of analytical initiatives from concept to execution. You will proactively gather business requirements, define key metrics, and coordinate across teams (like Data Science and BI) to deliver comprehensive solutions.
Who you are
The Growth Mindset: You treat the business segment like your own company. You proactively identify anomalies and hunt for solutions before they become problems.
Technically Elite: Expert-level SQL and strong Product Analytics (GA4, Amplitude, or similar) and A/B testing experience (Optimizely, Statsig, or similar).
Modern Data Workflows: Experience with cloud data warehouses (e.g., Snowflake) and collaborating via version control (GitHub) to maintain a highly scalable and organized environment.
We expect you to leverage modern AI tools. You’re already using Cursor, Claude Code, or similar in your workflows to close the gap between data and execution.
Solid understanding of statistical measures, including p-values, confidence intervals, and causal inference.
Proficiency with Python and dashboarding tools (e.g., Tableau, Power BI, or similar) is recommended.
Executive Storytelling: You don't just share data; you influence strategy. You are highly skilled at translating complex statistical analysis and analytical frameworks into crisp, high-impact narratives that command the attention of senior and executive leadership. You focus heavily on the "so what" and actively guide business decisions rather than just answering ad-hoc data requests.
Experience: 3-5+ years of experience in a highly quantitative analytical role (e.g., Product Growth, Marketing Analytics, Revenue Operations, Monetization, or Data Science), ideally within a B2B or B2C SaaS or subscription-based business model.
Bachelor’s degree (preferably in a quantitative field such as analytics, business, math, statistics, economics or computer science); Master's a plus.