Paytm: Analytics Lead- User Growth I Exp- 8- 10 Years — Noida, Uttar Pradesh

About Paytm

Paytm is an Indian digital payments and financial services firm under parent One97 Communications. Its services handle consumer payments through UPI and its app-based wallet, merchant acceptance and payment gateways, with bill payments, ticketing and other commerce services on the same platform. Headquartered in Noida, the company serves consumers and merchants across India, and its employer feed lists technology and product roles for the payments ecosystem.

The position and its setting

Paytm lists Analytics Lead- User Growth I Exp- 8- 10 Years in Noida, Uttar Pradesh, under reference 4c41d1d2-ed6b-4726-95b8-beb76999ee26. The details below separate the work described by the employer from essential conditions, preferred experience and practical preparation advice.

• Department: Growth
• Employment type: Full-time Employment
• team: User Growth

Responsibilities and work described

• 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
• Analysis: cohorts, journeys, segments and behavioural trends to improve customer lifetime value and repeat transactions
• Building: 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
• Research / execution: 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
• Analysis: A/B tests and control-group experiments to isolate true incrementality
• Metrics, Dashboards & Models
• Building: 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

Essential requirements and candidate background

• 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: large-scale transactional and behavioural datasets in a high-velocity consumer business
• 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
• 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
• 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
• 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

Education and qualification routes

• Degree / qualification: MBA or Master’s in a quantitative field preferred

Preferred experience and additional strengths

• Exposure: wealth, investments, savings or commodity-linked products
• Experience: SIP / recurring-payment analytics, including mandate and autopay behaviour
• Familiarity: pricing, margin and unit-economics analysis
• Experience mentoring junior analysts

Location, schedule and contract conditions

• India’s largest digital lending story is brewing here
• It’s your opportunity to be a part of the story!
• Advertised location: Noida, Uttar Pradesh

Pay and application dates

A verified salary figure is not established in this article. An online estimate for another Analytics Lead- User Growth I Exp- 8- 10 Years vacancy is not an offer for reference 4c41d1d2-ed6b-4726-95b8-beb76999ee26; use the employer’s own pay disclosure and recruitment communication.

A closing date is not confirmed in this article. Check the current employer page before submitting: an undated posting can change or be withdrawn.

How to apply to Paytm

Applications follow the official employer page linked below.

Open the official Paytm posting below and match the title and reference 4c41d1d2-ed6b-4726-95b8-beb76999ee26.

Compare your qualifications and experience with the essential conditions for the Noida, Uttar Pradesh position, then read the preferred criteria separately.

Prepare an accurate CV and the supporting items requested in that employer’s application. Provide only information and documents you are authorised to share.

Use the employer’s application option, complete the required fields and review the submission. Retain the acknowledgement when one is provided. Job Alerts World does not receive the application.

Practical preparation: Python

Python work is easier to assess through a concrete example than a list of libraries. Explain the problem, the input data, the parts you implemented and how you checked the output. Include a repository or a short technical note when you can share it.

Relevant skills

• Python
• SQL
• Hive
• Excel
• ISO
• Power BI
• Tableau
• investment
• marketing
• stakeholder management