Own the full analytics stack: track user acquisition, engagement, retention, and monetization metrics across free and premium tiers.
Deep-dive into listening behavior to quantify what makes an episode “great” and how personalization impacts completion rates, repeat usage, and subscription conversion.
Build and maintain dashboards (we use tools like Amplitude, Mixpanel, Snowflake, dbt, and Looker/Tableau) that product, growth, and leadership rely on daily.
Design and analyze A/B tests for recommendation algorithms, paywalls, onboarding flows, and content discovery features.
Partner closely with engineering and product to instrument new events, define KPIs for upcoming features (e.g., voice interaction mode, visual explainers), and surface actionable insights.
Identify leading indicators of churn, virality, and LTV; propose and validate interventions.
Help shape our data warehouse and establish best practices as we transition from startup chaos to scalable infrastructure.

3–6 years of hands-on analytics experience, ideally at a consumer tech or edtech company.
Advanced SQL skills (you write clean, efficient queries on large datasets).
Proficiency in Python or R for analysis and scripting; experience with dbt is a strong plus.
Comfortable with product analytics platforms (Amplitude, Mixpanel, Heap) and visualization tools (Looker, Tableau, Mode).
Strong statistical foundation and rigorous approach to experimentation and causal inference.
Excellent communicator who can translate complex findings into clear recommendations for non-technical stakeholders.
Genuine curiosity about user behavior and a bias toward action—early-stage environment means you’ll wear multiple hats and ship insights quickly.
Bonus: experience with recommendation systems, audio/content platforms, or freemium monetization.

Direct impact: your analyses will shape product roadmap, pricing, and growth strategy at a critical inflection point.
High ownership: small team, big problems, no bureaucracy.
Mission that matters: help democratize access to research and accelerate scientific progress.
Competitive salary, meaningful equity, flexible remote/hybrid work, and learning budget.

Data Analyst

Key skills