Job Description

About the role:

INDmoney is on a mission to make every Indian financially independent. As a Senior Product Manager for Investment Products, you will own the end to end product experience across one of the investment verticals. making complex financial journeys feel simple, trustworthy, and rewarding for first time and seasoned investors alike.

You will sit at the intersection of data, design, and distribution and be directly accountable for investor conversion, engagement, and retention metrics.

What you will own

Define and execute the product roadmap for investment verticals including Indian stocks, ETFs, IPOs, US stocks, mutual funds, bonds, and NPS, with clear OKRs tied to investor conversion, AUM growth, and ticket reduction.
Simplify the investing experience for the ordinary Indian user: reduce cognitive load, build financial literacy into the product, and design journeys that convert intent into action
Translate user research, support data, and funnel analytics into prioritised, well scoped product opportunities not just feature lists
Write high quality PRDs and user stories using LLM tooling, collaborating closely with design and engineering to maintain a high bar for execution
Partner with growth, marketing, and ops to run experiments that move conversion and retention metrics meaningfully
Identify friction, drop offs, and trust signals across the investment onboarding and transaction funnel and fix them systematically
Build and monitor dashboards to track cohort health, activation milestones, and feature adoption and create a rhythm of weekly data reviews with your team
Stay deeply informed on regulatory changes (SEBI, AMFI, RBI) and competitive product moves; translate these into product action faster than the market

What we are looking for

Core skills:

Simplification instinct proven ability to take a complex financial product (SIP, F&O, ESOP liquidation, US stock fractional buying) and design an experience that an ordinary Indian in Tier 2 city can complete confidently in under 3 minutes
Data fluency comfortable querying SQL Redshift, building Mixpanel funnels, and turning raw numbers into a crisp narrative with a clear action not a slide full of charts
Investment domain depth working knowledge of equities (NSE BSE), US stocks, mutual funds (direct vs regular, STP, SWP), bonds, NPS tiers, tax implications (LTCG, STCG, DTAA) and how they map to user mental models
AI native product thinking uses LLM tools (Claude, ChatGPT, Gemini) to draft PRDs, generate user stories, create wireframe briefs, and accelerate research synthesis not as a novelty but as a core part of the workflow
Metrics ownership genuinely comfortable being held accountable to targets such as D30 investor activation rate, AUM per activated user, KYC to first investment conversion, and support ticket reduction per feature
Cross functional drive ability to influence without authority across design, engineering, compliance, and marketing teams; can hold a weekly sprint rhythm and unblock execution

Experience:

5–9 years of product management, with at least 3 years in consumer fintech, wealth tech, or a high transaction volume product
Prior ownership of a product with measurable conversion or retention metrics you should be able to quote the before after numbers for at least two initiatives
Experience working with compliance and regulatory constraints without letting them become roadblocks
Exposure to growth product loops referrals, nudges, personalised recommendations, or re engagement flows
Deep personal investing experience across multiple asset classes
Experience building ML AI assisted product features (e.g. personalised portfolio recommendations, smart alerts, risk profiling)
Has shipped a mobile first investment products in India

What success looks like in 90 days

Deep familiarity with the end to end INDmoney investment funnel, knows where users drop, why, and has a prioritised hypothesis list
At least one impactful initiative shipped or in final testing, with a defined metric it is moving
Has built a strong working relationship with design, data, and engineering pods
Weekly data review ritual established, funnel anomalies surfaced proactively