Senior Manager I, Analytics
Bangalore
Razorpay
Online Payments India: Start Accepting Payments Instantly with Razorpay's Payment Suite, which Supports Netbanking, Credit Card & Debit Cards, UPI etc.Razorpay was founded by Shashank Kumar and Harshil Mathur in 2014. Razorpay is building a new-age digital banking hub (Neobank) for businesses in India with the mission is to enable frictionless banking and payments experiences for businesses of all shapes and sizes. What started as a B2B payments company is processing billions of dollars of payments for lakhs of businesses across India.
We are a full-stack financial services organisation, committed to helping Indian businesses with comprehensive and innovative payment and business banking solutions built over robust technology to address the entire length and breadth of the payment and banking journey for any business. Over the past year, we've disbursed loans worth millions of dollars in loans to thousands of businesses. In parallel, Razorpay is reimagining how businesses manage money by simplifying business banking (via Razorpay X) and enabling capital availability for businesses (via Razorpay Capital).The Role
The Analytics Team at Razorpay is a group of curious problem solvers who drive data-led decision-making across the organization. We work on high-impact business challenges, leveraging data mining, experimentation, statistical analysis, and machine learning where applicable.
As a Senior Manager - Analytics, you will lead a team of analysts, partnering closely with Business, Marketing & Product teams to drive insights, optimize strategies, and create measurable impact. This role is ideal for someone who thrives on solving ambiguous problems, mentoring high-performing teams, and using data to influence business outcomes.
Key Responsibilities
1. Leadership & People Management
- Lead, mentor, and develop a team of analysts, fostering a culture of structured problem-solving and analytical excellence.
- Set high performance benchmarks, create learning opportunities, and ensure a growth-oriented team environment.
- Own stakeholder management and prioritization, balancing quick wins with long-term strategic impact.
- Enable the team to work effectively with cross-functional partners, translating business needs into clear analytical roadmaps.
2. Business/Product Analytics
- Build a deep understanding of the stakeholder functions - business/sales/marketing/product, and the levers to identify high-impact opportunities.
- Define key metrics, ensure accurate tracking & instrumentation, and work with engineering teams to improve data quality.
- Conduct exploratory analyses and deep dives to uncover actionable insights that drive revenue, user growth, and engagement.
- Work closely with sales and marketing teams to optimize campaign performance, measure ROI, and improve customer acquisition and retention.
3. Experimentation & Data Strategy
- Design and analyze A/B tests to measure the impact of new product features, campaigns, and strategic initiatives.
- Ensure statistical rigor in analyses, experiment design, and hypothesis testing.
- Drive self-serve analytics using tools like Tableau to empower stakeholder teams
- Collaborate with data engineering teams to improve data pipeline efficiency, scalability, and governance.
- Drive central analytics initiatives to improve the quality, efficiency, and scalability of analytics across teams.
What We’re Looking For
Mandatory Qualifications
- 7+ years of experience in Analytics & Data Science, with 4+ years in a Tech ecosystem (fintech, SaaS, e-commerce, or consumer tech preferred).
- People & senior stakeholder management experience – mentoring teams, and collaborating with senior stakeholders.
- Expertise in SQL and Python for large-scale data analysis.
- Experience working with structured, semi-structured, and unstructured data
- Hands-on experience in A/B testing, hypothesis testing, and statistical analysis.
- Experience in Sales & Marketing Analytics (e.g., campaign attribution, CAC/LTV modeling, customer segmentation)
- Proven ability to translate complex analytical findings into clear business recommendations and communicate them effectively.
- Exposure to development of machine learning models for use cases like customer segmentation, churn prediction, or personalization.
Preferred Qualifications
- Working knowledge of Product Analytics (e.g., funnel analysis, feature experimentation).
- Familiarity with web analytics, performance & growth marketing
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing Banking Data analysis Data Mining Data quality Data strategy E-commerce Engineering FinTech Machine Learning ML models Python SQL Statistics Tableau Testing Unstructured data
Perks/benefits: Career development Startup environment
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