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Paytm, India's leading mobile payments and financial services company, is seeking an Analytics Lead to drive data-led growth across user acquisition, retention, churn, revenue and GMV lifecycle. This is a senior individual contributor role focused on delivering deep analytical insights that directly impact business outcomes.
You will own analytics across multiple dimensions: business insights and growth (identifying key drivers for acquisition, engagement, retention and churn reduction); customer and lifecycle analytics (cohort analysis, retention frameworks, churn diagnosis); campaign efficacy and attribution (measuring campaign performance, ROI analysis, A/B testing); and metrics/dashboards/models (building business metrics, dashboards and forecasting models). You'll partner closely with Product, Marketing, Growth, Data Warehouse and Business teams to translate complex data into actionable narratives for senior stakeholders.
Key responsibilities include driving revenue and GMV growth aligned with annual operating plans, building cohort and retention frameworks (D0/D7/D30, monthly triangles), conducting funnel and attribution analysis, reconciling promotional spend against incremental GMV, analyzing A/B tests and control-group experiments, owning metric definitions and data integrity, developing forecasting and scenario models, and delivering clear analytical inputs for management business reviews.
You will work with large-scale transactional and behavioral datasets in a high-velocity consumer business, partnering with high-performing product, design and engineering teams in one of India's most dynamic fintech spaces.
REQUIREMENTS:
- 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 behavioral datasets in high-velocity consumer businesses
- Advanced SQL: complex joins, window functions, CTEs, query optimization on distributed datasets (Trino/Presto/Hive/Redshift/BigQuery)
- Python proficiency: pandas, numpy, statistical testing, automation; modeling libraries a plus
- Advanced Excel: pivots, complex formulas, macros
- Data modeling: dimensional modeling, star/snowflake schemas, event and funnel data structures, metric-layer design
- Data visualization: Tableau, Power BI, Superset or equivalent
- Product and web analytics: Google Analytics, CleverTap, Mixpanel, Amplitude or Firebase
- Strong command of cohort analysis, funnel analysis, retention curves, LTV modeling, attribution methodologies and experiment design
- Comfort with significance testing, regression, segmentation and clustering techniques
- Commercial instinct and excellent communication skills
- Bachelor's in Engineering, Statistics, Mathematics, Economics or related quantitative discipline; MBA or Master's in quantitative field preferred
GOOD TO HAVE:
- Exposure to wealth, investments, savings or commodity-linked products
- Experience with SIP/recurring-payment analytics, mandate and autopay behavior
- Familiarity with pricing, margin and unit-economics analysis
- Experience mentoring junior analysts
