Senior Manager I, Analytics

Razorpay is one of India’s leading full-stack financial technology companies, powering the way businesses move, manage, and grow money. Founded in 2014 by Harshil Mathur and Shashank Kumar with a simple vision - to simplify payments for Indian businesses - we’ve since grown into a fintech powerhouse driving India’s digital payment revolution.

Razorpay powers millions of businesses with a smarter, scalable stack that goes beyond transactions to help them truly build and grow.

From building AI-native agentic payments, to AI-assisted fraud detection and real-time risk intelligence to automated reconciliation, smart payouts, and predictive financial insights, we are embedding intelligence across our stack to make money movement faster, safer, and more efficient. In close collaboration with ecosystem partners - including banks, networks, regulators - we are pioneering industry-first solutions that are shaping the next era of fintech

Across India, Singapore and Malaysia, our products span everything from seamless checkouts to payroll automation - powering a fintech ecosystem that’s redefining how money moves across Asia.

Today, that ecosystem supports everyone from early-stage startups to some of India’s largest enterprises, enabling them to accept, process, and disburse payments at scale while expanding into new ways of managing money more efficiently.

Our scale speaks volumes: Razorpay processes $180+ billion in annualized transactions, powering leading businesses like Airbnb, Facebook, WhatsApp, Airtel, CRED, BookmyShow, Zomato, Swiggy, Lenskart, Mirae Asset Capital markets, Indian Oil, National Pension Scheme - and over 100 of India’s unicorns. With strong roots in India and growing operations in Southeast Asia, we are shaping the next chapter of financial technology across the region.

We are backed by global investors including GIC, Peak XV Partners (formerly Sequoia Capital India & SEA), Tiger Global, Ribbit Capital, Matrix Partners, MasterCard, and Salesforce Ventures, having raised over $740 million to date. Strategic acquisitions - including Ezetap (POS and offline payments), Curlec (Malaysia expansion), BillMe (digital invoicing), and POP (rewards-first UPI) - along with earlier moves in fraud prevention, payroll, and lending, have further strengthened our platform and widened our footprint across Asia.

But what truly sets Razorpay apart is our culture. At Razorpay, ownership is our oxygen - you own what you build, with no micromanagement or red tape, just the runway to make your ideas fly. Learning is a lifestyle - if you’re curious, you’ll feel at home here. People > Pedigree - we hire for attitude, hustle, and hunger more than degrees. Transparency thrives over titles - this is where interns question CXOs and CXOs say “thank you.” Guided by our values of Customer First, Autonomy & Ownership, Agility with Integrity, Transparency, Challenging the status quo and a strong belief that Razorpay grows with Razors,  you’ll be part of a 3000+ strong team building not just products, but the financial infrastructure of the future.

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

Strategic Analytics & Business Insights

• Develop a deep understanding of ad network performance, customer engagement, and marketing analytics, identifying high-impact opportunities for optimization.
• Define and refine key business metrics, ensuring accurate tracking, instrumentation, and data quality in collaboration with engineering teams.
• Conduct exploratory analyses, cohort studies, and funnel deep dives to uncover actionable insights that drive campaign efficiency, customer LTV, and retention strategies.
• Work closely with Sales, Marketing, and Growth teams to optimize campaign performance, measure ROI, and improve attribution modeling and bid optimization.
• Structure problem-solving frameworks that drive measurable impact across customer engagement initiatives.

2. Experimentation & Optimization

• Design and analyze A/B tests to measure the impact of marketing campaigns, product features, and engagement strategies.
• Ensure statistical rigor in all analyses, experiment designs, and hypothesis testing to validate growth initiatives.
• Develop scalable methodologies for predictive modeling, churn analysis, and personalized engagement strategies.

3. Data Strategy & Automation

• Build self-serve analytics solutions using Tableau, SQL, and Python, empowering stakeholders with real-time insights.
• Collaborate with data engineering teams to enhance data pipeline efficiency, scalability, and governance.
• Drive central analytics initiatives that improve efficiency, automation, and standardization across analytics workflows.

What We’re Looking For

Mandatory Qualifications

• 8+ years of experience in Analytics & Data Science, with 4+ years in Tech (AdTech, MarTech, Consumer Tech, FinTech, SaaS, or E-commerce preferred).
• Mandatory experience in Ad Network Analytics – including campaign attribution, bid optimization, CAC/LTV modeling, and ad spend efficiency.
• Expertise in SQL, Python, and Tableau for large-scale data analysis.
• Proven track record in marketing, growth, and engagement analytics, including customer segmentation, funnel optimization, and retention modeling.
• Experience in A/B testing, hypothesis testing, and statistical modeling.
• Ability to translate complex analytical insights into clear, data-driven business recommendations for senior stakeholders.

Preferred Qualifications

• Experience in product analytics, including feature experimentation and user behavior analysis.
• Exposure to machine learning models for churn prediction, personalization, and marketing automation.
• Working knowledge of web analytics, growth marketing, and performance marketing strategies.