Head Analytics(GM/ AVP) , Paytm Money

About Us

Paytm is India’s leading payments Super App, offering consumers and merchants a wide range of financial services. A pioneer of the mobile QR payments revolution, Paytm’s mission is to bring half a billion Indians into the mainstream economy through technology-led financial inclusion.

Paytm Money is the wealth-tech arm of Paytm, enabling users to invest in mutual funds, equities, and derivatives seamlessly. Owned by One97 Communications, founded by Vijay Shekhar Sharma, the company is headquartered in Noida and backed by leading global investors.

Role Overview

We are looking for a strategic, business-oriented, and AI-forward Analytics Leader to drive data-led and AI-powered decision-making for Paytm Money across equities, mutual funds, and derivatives.

This role will define and lead the analytics vision across user growth, trading behavior, portfolio analytics, customer lifecycle, monetization, and product experience, while partnering closely with Product, Growth, Business, Risk, and Engineering teams to scale Paytm Money’s wealth platform.

The ideal candidate will bring deep expertise in financial markets, broking platforms, and investment products, along with strong experience in building scalable analytics functions. In addition, this leader should have worked intensively on AI-led modeling, predictive decision systems, AI adoption across analytics workflows, and data models designed for advanced analytics and machine learning use cases.

This is not just a reporting or dashboarding role. It is a leadership role focused on building a proactive, predictive, and AI-enabled analytics engine that helps the business make faster, sharper, and more scalable decisions.

Key Responsibilities

1. Analytics Strategy, AI Vision & Business Impact

·   Define and own the analytics and decision intelligence roadmap aligned with Paytm Money’s growth, engagement, and revenue goals.

·   Translate business problems across acquisition, activation, trading behavior, retention, and monetization into structured analytical and AI-led problem-solving frameworks.

·   Drive a data-first and AI-enabled decision culture across Product, Growth, Business, Marketing, Risk, and Finance teams.

·   Evolve the analytics function from descriptive reporting to predictive and prescriptive decision support.

·   Identify high-impact use cases where AI/ML can materially improve conversion, retention, customer engagement, monetization, or operational efficiency.

2. Investment, Broking & Customer Lifecycle Analytics

·   Analyze user behavior across equities, derivatives, and mutual funds journeys spanning onboarding, KYC, activation, investing/trading, engagement, and repeat usage.

·   Build deep insights on trading frequency, portfolio behavior, SIP trends, churn, investor segmentation, and cohort performance.

·   Develop analytical frameworks for order flow, liquidity behavior, margin usage, derivatives participation, and investment lifecycle progression.

·   Use behavioral, tr