The Role
Lead growth analytics across acquisition, retention, churn, revenue, and GMV. Analyze cohorts, funnels, campaigns, attribution, experiments, and customer behavior to identify growth opportunities and improve lifetime value. Build metrics, dashboards, forecasting models, and data frameworks while ensuring data integrity. Partner with Product, Marketing, Growth, Data Warehouse, and business teams to translate complex analysis into actionable recommendations, support planning and business reviews, and drive measurable commercial outcomes.
Summary Generated by Built In
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-
KEY RESPONSIBILITIES
Business Insights & Growth
- Drive data-led growth across the acquisition, retention, churn, revenue and GMV lifecycle.
- Own deep-dive analytics to identify key drivers and opportunities for acquisition, engagement, retention and churn reduction.
- Drive Revenue and GMV growth in line with the Annual Operating Plan (AOP) through actionable insights and growth recommendations.
Customer & Lifecycle Analytics
- Analyse cohorts, journeys, segments and behavioural trends to improve customer lifetime value and repeat transactions.
- Build cohort and retention frameworks (D0/D7/D30, monthly triangles) across new, reactivated and repeat users.
- Diagnose churn and cancellation drivers and recommend structural fixes, not surface-level corrections.
Campaign Efficacy & Attribution
- Measure and optimize campaign efficacy — identifying the right segments, propositions, channels and levers to maximize incremental GMV and revenue.
- Conduct funnel, cohort, campaign and attribution analysis to identify performance gaps and recommend corrective actions.
- Reconcile promotional burn against incremental GMV; establish ROI and cost-per-incremental-user benchmarks by campaign and segment.
- Analyse A/B tests and control-group experiments to isolate true incrementality.
Metrics, Dashboards & Models
- Build and track key business metrics, dashboards, performance frameworks and analytical models to monitor growth against AOP.
- Own metric definitions and data integrity; maintain a single source of truth across teams.
- Develop forecasting and scenario models for GMV, revenue and user base to support planning cycles.
Stakeholder Partnership
- Partner closely 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 MBRs and business reviews — with a clear storyline, not just charts.
REQUIREMENTS
Experience
- 8-10 years of experience in business analytics, growth analytics or data science — preferably in consumer internet, fintech, e-commerce or financial services.
- Demonstrated ownership of a product vertical or growth charter with measurable business impact.
- Experience with large-scale transactional and behavioural datasets in a high-velocity consumer business.
Technical Skills
- SQL — advanced: complex joins, window functions, CTEs and query optimization on large distributed datasets (Trino/Presto/Hive/Redshift/BigQuery).
- Python — pandas, numpy, statistical testing and automation; modelling libraries a plus.
- Advanced Excel — pivots, complex formulas & macros
- Data Modelling — dimensional modelling, star/snowflake schemas, event and funnel data structures, metric-layer design.
- Data Visualization — Tableau, Power BI, Superset or equivalent; dashboards that get used, not just built.
- Product & Web Analytics — Google Analytics, CleverTap, Mixpanel, Amplitude or Firebase for funnel and journey analysis.
Analytical & Business Capabilities
- Strong command of cohort analysis, funnel analysis, retention curves, LTV modelling, attribution methodologies and experiment design.
- Comfort with significance testing, regression, segmentation and clustering techniques.
- Commercial instinct — able to connect a metric movement to the underlying business mechanic and the money at stake.
- Excellent communication; able to defend a recommendation with evidence in front of senior leadership.
Education
- Bachelor’s in Engineering, Statistics, Mathematics, Economics or a related quantitative discipline. MBA or Master’s in a quantitative field preferred.
GOOD TO HAVE
- Exposure to wealth, investments, savings or commodity-linked products.
- Experience with SIP / recurring-payment analytics, including mandate and autopay behaviour.
- Familiarity with pricing, margin and unit-economics analysis.
- Experience mentoring junior analysts.
CORE COMPETENCIES
- Diagnostic mindset — pushes past the symptom to the root cause.
- Rigour — validates counts and stress-tests assumptions before publishing.
- Ownership — treats the business target as their own.
- Clarity — reduces complexity to a decision, not a data dump.
- Constructive dissent — challenges assumptions and targets with data, early.
Why join us:
Work with a high-performing and passionate product, design, and engineering team.
Shape the future of credit for millions of users.
Build at scale in one of India’s most dynamic and regulated spaces.
Flexible and inclusive work environment with fast decision-making and ownership.
Compensation:
If you are the right fit, we believe in creating wealth for you with enviable 500 mn+ registered users, 25 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants – and we are committed to it. India’s largest digital lending story is brewing here. It’s your opportunity to be a part of the story!
Skills Required
- 8-10 years of experience in business analytics, growth analytics, or data science
- Experience in consumer internet, fintech, e-commerce, or financial services
- Ownership of a product vertical or growth charter with measurable business impact
- Experience working with large-scale transactional and behavioral datasets in a high-velocity consumer business
- Advanced SQL, including complex joins, window functions, CTEs, and query optimization
- Python proficiency with pandas, NumPy, statistical testing, and automation
- Advanced Excel skills, including pivots, complex formulas, and macros
- Experience with dimensional data modeling, star and snowflake schemas, event and funnel structures, and metric-layer design
- Experience building data visualizations and dashboards using Tableau, Power BI, Superset, or equivalent tools
- Experience with product and web analytics tools such as Google Analytics, CleverTap, Mixpanel, Amplitude, or Firebase
- Strong knowledge of cohort analysis, funnel analysis, retention curves, LTV modeling, attribution, and experiment design
- Experience with significance testing, regression, segmentation, and clustering
- Bachelor's degree in Engineering, Statistics, Mathematics, Economics, or a related quantitative discipline
- MBA or master's degree in a quantitative field
- Experience with wealth, investments, savings, or commodity-linked products
- Experience with SIP or recurring-payment analytics, including mandate and autopay behavior
- Familiarity with pricing, margin, and unit-economics analysis
- Experience mentoring junior analysts
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The Company
What We Do
Paytm started the Digital Revolution in India. And we went on to become India’s leading Payments App. Today, more than 20 Million merchants & businesses are powered by Paytm to Accept Payments digitally. This is because more than 300 million Indians use Paytm to Pay at their stores. And that’s not all, Paytm App is used to Pay bills, do Recharges, Send money to friends & family, Book movies & travel tickets. With innovations to Financial services & products in pipeline, this is but one of the milestones achieved towards our mission – to bring 500 million unserved and underserved Indians to the mainstream economy.
