As a Data Analyst, you’ll work closely with cross-functional teams—including Product, Marketing, Sales, User Acquisition, and Senior Leadership—to dig into business trends, analyze A/B tests, and provide data-backed recommendations. You should be passionate about leveraging data to tell a story, solve problems, and uncover new opportunities.

What You’ll Do

• Analyze product performance, customer behavior, and business trends to surface insights and opportunities.
• Partner with Marketing and Growth teams to help optimize acquisition strategies based on data-driven insights.
• Build and interpret payback curves and LTV forecasts to assess campaign profitability and long-term value.
• Perform cohort analyses to understand user retention, churn patterns, and behavioral segmentation.
• Design and evaluate A/B and multivariate experiments to optimize product features and user experiences.
• Conduct root cause analysis to help teams troubleshoot unexpected outcomes or KPI movements.
• Partner with Product Managers to define KPIs, set success criteria, and build dashboards for monitoring.
• Communicate findings clearly and effectively to both technical and non-technical audiences.
• Build and maintain dashboards and reports using BI tools (especially Looker).
• Write complex and efficient SQL queries to extract and analyze data across multiple sources.

What We’re Looking For

• 3–5 years of experience in product or business analytics, preferably in a fast-paced, data-driven environment.
• Strong SQL skills – you should be able to independently pull, transform, and analyze large datasets.
• Experience with user acquisition analytics, including CAC, payback windows, and LTV modeling.
• Familiarity with retention/churn metrics and methods for evaluating cohort health over time.
• A strong sense of ownership and a proactive, collaborative mindset.
• A structured approach to problem-solving and a sharp eye for spotting trends, anomalies, and opportunities in data.
• Experience with Looker (or similar BI tools like Tableau or Power BI).
• Excellent communication skills – you should be able to tailor messaging to various stakeholders, including senior leadership.
• Experience supporting product experimentation and interpreting test results.
• Basic knowledge of Python (e.g., pandas, NumPy, Jupyter) is a plus, but not required.
• Curiosity, humility, and a desire to keep learning and growing – technically and professionally.