Product Analyst

We are looking for a curious, data-obsessed Product Analyst who turns raw product data into sharp, continuous insights for our Ed-Tech

platform. You will own core metrics, automate reporting, build dashboards, and partner with product, growth, and engineering — and use

AI tools to move from question to answer to action faster than a traditional analytics team.

• Analyze & uncover insights — dig into learner behavior, course performance, funnels, and engagement to surface patterns the team

can act on.

• Own the metrics — define, track, and defend product KPIs; build the source of truth for activation, retention, conversion, and learning

outcomes.

• Automate reporting — replace manual pulls with self-serve dashboards, scheduled reports, and alerting so the team gets answers,

not tickets.

• Build dashboards — design clean, intuitive views in Metabase / Looker / Tableau / Power BI that non-analysts actually use.

• Monitor data pipelines — watch data quality, freshness, and integrity; flag anomalies and partner with engineering on fixes.

• AI-led analytics — use Claude, ChatGPT, Cursor, and Claude Code to draft SQL, accelerate exploration, generate scripts, and ship

analyses end-to-end.

• Ask the next question — bring genuine curiosity — question numbers, challenge assumptions, and translate findings into clear,

actionable narratives.

• 1–4 years in analytics, product analytics, BI, or data science roles.

• Strong SQL and Python (pandas, NumPy) — comfortable wrangling messy product data and writing efficient queries at scale.

• Hands-on, daily use of AI tools for analytics — Claude, ChatGPT, Cursor, Claude Code — for SQL drafting, code generation, and faster

output delivery.

• Experience with a BI tool (Metabase, Looker, Tableau, Power BI) and a product analytics platform (Mixpanel, Amplitude, GA4).

• Solid grounding in statistics, A/B testing, and experimentation — knowing when a result is real.

• Sharp written communication — distilling complex analyses into clean memos, charts, and recommendations.

• Bachelor's degree in a quantitative field; high agency, strong ownership, and a learning-by-shipping mindset.

• Experience in Ed-Tech, data science, or marketplace / community products.

• Familiarity with dbt, Airflow, or modern data stack tooling for reliable pipelines.

• Built or maintained data quality / observability frameworks (Great Expectations, Monte Carlo, Soda, etc.).

Shape decisions on products used by millions of learners · high ownership with product & leadership · fast, learning-driven culture ·

competitive compensation and growth.

Apply now and help turn data into the next big bet in AI-native learning