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Paytm Labs

Digital payments, loans, investments, and insurance

Business Analytics

Data Science +1Confirmed live in the last 24 hours
Full-timeNoida, Uttar Pradesh, IndiaNo salary listedIn-person

About the Job

Requirements

  • The candidate must have 5–7 years of experience in business analytics, growth analytics, or data science, preferably in consumer internet, fintech, e-commerce, or financial services.
  • The candidate must have demonstrated ownership of a product vertical or growth charter with measurable business impact.
  • The candidate must have experience with large-scale transactional and behavioural datasets in a high-velocity consumer business.
  • The candidate must have advanced SQL skills, including complex joins, window functions, common table expressions, and query optimization on large distributed datasets using Trino, Presto, Hive, Redshift, or BigQuery.
  • The candidate must have Python skills, including pandas, numpy, statistical testing, and automation; modelling libraries are a plus.
  • The candidate must have advanced Excel skills, including pivots, complex formulas, and macros.
  • The candidate must understand data modelling, including dimensional modelling, star/snowflake schemas, event and funnel data structures, and metric-layer design.
  • The candidate must have data visualization skills using Tableau, Power BI, Superset, or equivalent, and experience building dashboards that are used.
  • The candidate must have product and web analytics experience using Google Analytics, CleverTap, Mixpanel, Amplitude, or Firebase for funnel and journey analysis.
  • The candidate must have a strong command of cohort analysis, funnel analysis, retention curves, lifetime-value modelling, attribution methodologies, and experiment design.
  • The candidate must be comfortable with significance testing, regression, segmentation, and clustering techniques.
  • The candidate must be able to connect metric movements to underlying business mechanics and financial impact.
  • The candidate must be able to communicate recommendations with evidence to senior leadership.
  • A bachelor's degree in Engineering, Statistics, Mathematics, Economics, or a related quantitative discipline is required.

Responsibilities

  • Drive data-led growth across the acquisition, retention, churn, revenue, and gross merchandise value lifecycle.
  • Own deep-dive analytics to identify key drivers and opportunities for acquisition, engagement, retention, and churn reduction.
  • Drive revenue and gross merchandise value growth in line with the Annual Operating Plan through actionable insights and growth recommendations.
  • Analyse cohorts, journeys, segments, and behavioural trends to improve customer lifetime value and repeat transactions.
  • Build cohort and retention frameworks, including D0/D7/D30 and monthly triangles, across new, reactivated, and repeat users.
  • Diagnose churn and cancellation drivers and recommend structural fixes.
  • Measure and optimize campaign efficacy by identifying segments, propositions, channels, and levers to maximize incremental gross merchandise value and revenue.
  • Conduct funnel, cohort, campaign, and attribution analysis to identify performance gaps and recommend corrective actions.
  • Reconcile promotional burn against incremental gross merchandise value and establish return-on-investment and cost-per-incremental-user benchmarks by campaign and segment.
  • Analyse A/B tests and control-group experiments to isolate true incrementality.
  • Build and track key business metrics, dashboards, performance frameworks, and analytical models to monitor growth against the Annual Operating Plan.
  • Own metric definitions and data integrity, maintaining a single source of truth across teams.
  • Develop forecasting and scenario models for gross merchandise value, revenue, and user base to support planning cycles.
  • Partner with Product, Marketing, Growth, DWH, and Business teams to convert insights into measurable outcomes.
  • Translate complex data into clear, actionable narratives for senior stakeholders and drive data-backed decision-making.
  • Own analytical inputs for monthly business reviews and business reviews, with a clear storyline rather than just charts.

Desired Qualifications

  • Modelling libraries for Python.
  • An MBA or master's degree in a quantitative field.
  • Exposure to wealth, investments, savings, or commodity-linked products.
  • Experience with SIP or recurring-payment analytics, including mandate and autopay behaviour.
  • Familiarity with pricing, margin, and unit-economics analysis.
  • Experience mentoring junior analysts.

About the Company

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Paytm Labs

Digital payments, loans, investments, and insurance

Paytm Labs offers an integrated digital payments and financial services platform in India for individuals and businesses, covering UPI payments, mobile recharges, bill payments, ticket bookings, loans, investments, insurance, metro cards, and more. Users initiate payments or financial actions in the app, which are processed through UPI and payment gateways, with revenue from transaction fees and commissions on financial services. It differentiates itself through a large ecosystem of merchants and users, a wide range of services in one app, and a focus on customer support and trust. Its goal is to make a broad set of financial services easily accessible to mass-market users while growing revenue via payment processing and financial services partnerships at scale.

Company size
10,001+
Company stage
IPO
Headquarters
Noida, India
Founded
2014

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