Data Analyst (Mixpanel)

Responsibilities:

• Instrumentation and Data Quality: Audit our Mixpanel event taxonomy: what's tracked, what's broken, what's double-counted, and what's missing. Work with engineers to fix the tracking plan.
• Funnel Ownership: Own the activation funnel end to end: install → first app open → login/signup → first content view → first completed video → habit. Break each step down by source, device, geo, cohort, and exam category. Find the drops, size them in users and in rupees, and tell us where to fix first.
• Notifications and Lifecycle: Own notification opt-in, delivery, open rate, and downstream session quality by segment, by time of day, and by message type. Tell us who to send what and when, then prove it with a test rather than a hunch.
• ETL and Data Plumbing: Pull raw event data out of Mixpanel, join it with backend/Postgres data, campaign data, and content metadata. Build clean, reusable datasets so recurring questions take minutes, not days.
• Feature Measurement: For everything we ship: define the success metric and the guardrail metric before launch, and read the result honestly after, including when it's flat or negative. Recommend what to double down on and what to kill.
• Retention and Content Analytics: D1/D7/D30 retention curves, cohort behavior, session depth, completion rate per video, and which formats, topics, and lengths actually bring users back.
• End-to-End Ownership: Close the loop with a short weekly written view of what moved, why, and what we will do next week. Two pages, no fluff. An insight nobody reads is worth zero.
• Metrics You'll Live Inside: First app open, login/signup conversion, notification opt-in, delivery, CTR, activation rate, D1/D7/D30 retention, DAU/WAU/MAU and stickiness, session length and sessions per user, content completion rate, funnel drop-off by step, CAC and channel quality.

Requirements:

• Real Consumer Exposure: Hands-on work with a consumer/D2C mobile app's numbers; via an internship, a startup, a growth team, or a serious side project. You've seen real user data at real volume, not a Kaggle CSV.
• Product Analytics: Working knowledge of Mixpanel (strongly preferred), or Amplitude, CleverTap, MoEngage, Firebase, or GA4.
• SQL: Joins, CTEs, window functions, and cohort and funnel queries against PostgreSQL.
• Tooling: Excel/Google Sheets at a serious level and Python (pandas) for anything Sheets can't handle.
• Metric Judgement: You understand what a number means, not just how to compute it. You can explain why D1 retention and notification opt-in move together, what rising DAU with falling session length is telling you, and when a metric went up for a reason that isn't good news.
• Communication: You write clearly and argue from evidence. You're comfortable telling a founder their favorite feature isn't working.

Nice to Have:

• Previous experience in a high-growth, product-based startup and having seen their journey.
• Ability to incorporate AI tools into daily analytics workflows to drive efficiency and deliver higher quality outcomes.
• Edtech, content, short-video, or subscription consumer experience.
• A/B testing: designing a test, sizing it, calling it, and knowing when a result isn't significant.
• Exposure to Segment, CleverTap, MoEngage, AppsFlyer, or Branch attribution.
• Understanding of Bharat/Tier 2-3 user behavior, Hindi-first audiences, low-end Android, and patchy connectivity.

Skills

Amplitude, CleverTap, Firebase, Mixpanel, MoEngage, PostgreSQL, Python, SQL, pandas