What you will own:

You own the path from finding a drop-off to fixing it. Nobody hands you a ticket list.

CleverTap and lifecycle comms:

- Own CleverTap: event tagging standards, user properties, segments, journeys, content, variant testing and campaign setup.

- Build cohorts on behavior, credit profile, product holding and lifecycle stage.

- Run targeted campaigns across push, SMS, WhatsApp, email and in-app.

- Manage frequency caps and quiet hours so we do not push users into uninstalling or opting out.

- Make sure every message follows RBI fair practices rules, TRAI DLT templates and consent, and the DPDP Act.

Funnel diagnosis:

- Map the main funnels end to end: install to KYC to first drawdown, first CCBP payment, first UPI transaction, and repeat use.

- Find the steps where users drop off, size the loss in users and revenue, and rank which gaps to work on first.

- Pull your own data with SQL and CleverTap. Do not wait on an analyst for routine questions.

Fixing what you find:

- Decide whether a gap needs a message, an offer, a change to the product, or a combination.

- For product changes, work with design, product and engineering to ship it, and measure the result.

- Run A/B tests with proper control groups. Report the change in the metric against control, not raw conversion.

- Moving from manual campaigns to the personalization engine.

- Turn what works in manual campaigns into rules and test designs for the engine.

- Set the guardrails the engine runs within: message limits, banned combinations and compliance rules.

- Read the engine's results with the data team and decide what to scale, change or stop.

Must-haves:

- 4 - 7 years in growth, lifecycle or product roles at a consumer app with more than 1 million monthly active users.

- At least 2 years of hands-on work in CleverTap, MoEngage, WebEngage or Braze. You have built segments and journeys yourself, not just briefed someone who did.

- Writes SQL without help: joins, window functions and cohort retention queries.

- Has run A/B tests with holdout groups and can explain incremental lift, sample size, and why a test result might be wrong.

- Has shipped at least one product change, from PRD to release, that came from their own funnel analysis.

- Can point to a specific metric they moved and by how much, and explain how they know the change caused it.

Good-to-haves:

- Experience in lending or another regulated fintech product, especially activation and repeat drawdown for a credit line.

- Has worked under RBI fair practices rules, TRAI DLT and DND, or DPDP consent rules.

- Familiar with AppsFlyer or GA4, and how install source affects later behavior.

- Has worked with data science on propensity or uplift models, or on deciding which message goes to which user.

- Experience with rewards or loyalty programme.