Analytics Lead - UPI Product | Experience : 7-9 yrs

About Paytm Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology.

About the Role UPI is the backbone of India's digital payments revolution — and Paytm is one of its largest participants, processing hundreds of millions of transactions every month. We are looking for a Product Manager to join our UPI team and drive product strategy, user growth, and experience excellence across our UPI-powered flows. This role sits at the intersection of consumer behaviour, financial infrastructure, and regulatory nuance. You will own high-impact product surfaces and work closely with engineering, design, data, and business teams to ship products that millions of Indians use daily.

Key Responsibilities 1. Analytics Strategy & Ownership - Own the end-to-end analytics charter for one or more UPI surfaces — from metric definition to instrumentation to insight generation - Build and maintain the source-of-truth framework for north-star and guardrail metrics across the UPI funnel (initiation, authentication, success/failure, retention) - Partner with NPCI-mandated reporting requirements and ensure analytical rigor aligns with regulatory data standards - Lead a team of analysts, setting priorities, reviewing outputs, and raising the bar on analytical craft

2. Funnel, Growth & Behavioural Insights - Diagnose friction points across the UPI journey using deep-dive analysis, cohort studies, and funnel decomposition - Build engagement, frequency, and top-of-wallet models to inform product and growth strategy - Design analytical frameworks for discovery and nudge effectiveness as new UPI capabilities are adopted - Partner with design and product research to combine quantitative and qualitative signals into a single narrative

3. Platform Reliability & Scale Analytics - Define and monitor SLA, success-rate, and latency benchmarks; build alerting and anomaly-detection frameworks tied to these metrics - Build root-cause analysis playbooks for payment failure spikes and incident-linked drop-offs - Model traffic and failure patterns ahead of high-volume events (festive seasons, IPL, government disbursements) to support platform readiness

4. Experimentation & Decision Science - Own the experimentation backbone — design, power, and evaluate A/B tests across the UPI funnel - Drive a test-and-learn culture: hypothesis → experiment → read-out → scale, with statistically sound methodology - Build self-serve dashboards and tooling that let product, engineering, and business teams access trusted insights without analyst dependency - Proactively surface insights that shape upstream roadmap and prioritization decisions

Required Qualifications