# Deputy General Manager – Product Analyst Lead

- Link: https://100xfounder.com/job/paytm-deputy-general-manager-product-analyst-lead-950920/
- Published: 2026-09-14T11:24:37+05:30
- Author: Ishaan Vardhan

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 an Analytics Lead to join our UPI team and own the data
and insights charter that powers product, growth, and platform decisions across 
our UPI-powered [flows.This](http://flows.This) role sits at the intersection of
consumer behaviour, financial infrastructure, and large-scale data systems. You 
will build the analytical backbone for UPI — from funnel and cohort frameworks to
experimentation infrastructure — and work closely with product, engineering, data
science, and business teams to turn transaction-scale data into decisions that affect
millions of Indians [daily.](http://daily.Key)

[Key](http://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 generationBuild
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 standardsLead a team of analysts, setting priorities, reviewing 
outputs, and raising the bar on analytical craf

t**2. Funnel, Growth & Behavioural Insights**Diagnose friction points across the
UPI journey using deep-dive analysis, cohort studies, and funnel decompositionBuild
engagement, frequency, and top-of-wallet models to inform product and growth strategyDesign
analytical frameworks for discovery and nudge effectiveness as new UPI capabilities
are adoptedPartner 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 metricsBuild root-cause analysis playbooks for payment failure spikes and 
incident-linked drop-offsModel 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 funnelDrive a test-and-learn culture:
hypothesis → experiment → read-out → scale, with statistically sound methodologyBuild
self-serve dashboards and tooling that let product, engineering, and business teams
access trusted insights without analyst dependencyProactively surface insights that
shape upstream roadmap and prioritization decisions

Required Qualifications

7–9 years of analytics/data experience, with a mandatory focus on consumer-facing
products or fintech; prior experience in payments or UPI strongly preferred

Strong command of SQL and hands-on experience with product analytics tools (Mixpanel,
Amplitude, Metabase, or equivalent); working knowledge of Python/R for deeper statistical
analysis

Solid grounding in experimentation design — hypothesis framing, sample size/power
calculations, and interpreting A/B results correctlyProven ability to translate 
ambiguous business questions into structured analyses and clear, decision-ready 
recommendations

Experience building and owning dashboards and metrics frameworks at scale, including
data quality and governance practices

Strong written and verbal communication skills — ability to present findings crisply
to leadership and align cross-functional stakeholders

Experience managing or mentoring a team of analysts, with a demonstrated ability
to review work and raise analytical standards

Good to Have

Prior experience working in a UPI-regulated environment or with NPCI data/reporting
constructs

Exposure to large-scale transaction data systems and familiarity with data warehousing/
pipeline concepts (e.g., working with data engineering teams on instrumentation)

Experience with growth, lifecycle, or CRM-driven analytics

Familiarity with fraud/risk analytics in a payments context