Data + Product Analyst Intern

About the Role

We're building the future of education and are looking for someone who thrives in a fast-paced environment and is comfortable navigating ambiguity.

We run a consumer app that delivers short-form videos and bite-sized revision content for exam preparation — built for aspirants who study on a phone, in short bursts, largely across Tier 2/3 India. You won't just be pulling reports; you'll be the person who answers "what is actually happening in our app, and what should we do about it?" Ideally, you are someone who can take a vague question, turn it into a measurable one, and come back with an answer the team can act on the same week.

What You'll Do

• Instrumentation & Data Quality: Audit our Mixpanel event taxonomy — what's tracked, what's broken, what's double-counted, 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 & Lifecycle: Own notification opt-in, delivery, open rate and downstream session quality — by segment, by time of day, by message type. Tell us who to send what and when, then prove it with a test rather than a hunch.
• ETL & 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, read the result honestly after, including when it's flat or negative. Recommend what to double down on and what to kill.
• Retention & Content Analytics: D1/D7/D30 retention curves, cohort behaviour, 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 — what moved, why, what we 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

What You Bring

• 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, 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 favourite feature isn't working.

Nice to Have

• Previous experience in a high-growth, product-based startup and have 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 behaviour, Hindi-first audiences, low-end Android and patchy connectivity.

Culture Fit

• Adaptive to Ambiguity: You are comfortable working in a dynamic environment where requirements may shift. You can move forward without having every single detail defined upfront.
• Problem Solver: You view messy data and unexplained drops as puzzles to be solved.
• AI Evangelist: You are someone who moves faster with AI — spending enough time framing the problem and then letting the models do their magic, with proper guardrails (sanity checks and validation so we move fast without shipping wrong numbers).

What You Get

• Direct access to the founders. Your analysis reaches the people who decide, the same day.
• Full ownership of analytics — you're not the fourth analyst in a ticket queue.
• Visibility across the whole loop: acquisition, product, content and retention, in one place.
• Certificate, letter of recommendation, and a PPO for strong performers.