Lead Analytics Specialist
Razorpay
Data Science
Bengaluru, Karnataka, India
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.
Role:
Lead Analytics Specialist will work with the central analytics team at Razorpay. This will give you an opportunity to work in a fast-paced environment aimed at creating a very high impact and to work with a diverse team of smart and hardworking professionals from various backgrounds. Some of the responsibilities include working with large, complex data sets, developing strong business and product understanding and closely being involved in the product life cycle. Setting high standards in project management and mentoring analysts.
Responsibilities:
- You will work with large, complex data sets to solve open ended, high impact business problems using data mining, experimentation, statistical analysis, and related techniques machine learning as needed
- You would have/develop a strong understanding of the business & product and conduct analysis to derive insights, develop hypotheses and validate with sound rigorous methodologies or formulate the problem for modeling with ML.
- You would design and implement AI-augmented analytics workflows, including RAG pipelines over data dictionaries, LLM-assisted report generation, and auto-tagging of anomalies in ETL processes
- You would explore AI-driven RCA tools. e.g., dashboards that surface probable causes for metric drops using LLM and embedding-based approaches
- You would coach analysts on ethical and secure AI usage, including prompt best practices, output validation, and guardrails around LLM-generated code and insights
- You would be closely involved with the product life cycle working on ideation, reviewing Product Requirement Documents, defining success criteria, instrumenting for product features, Impact assessment and identifying and recommending improvements to further enhance the Product features
- You would expedite root cause analyses/insight generation against a given recurring use case through automation/self-serve platforms
- You will develop compelling stories with business insights, focusing on strategic goals of the organization
- You will work with Business, Product and Data engineering teams for continuous improvement of data accuracy through feedback and scoping on instrumentation quality and completeness
- Set high standards in project management; own scope and timelines for the team
- Take responsibility for skill-building within the organization (training, process definition, research of new tools and techniques etc.)
- Mentoring analysts within the team to deliver effectively, incubating new ideas.
Mandatory Qualifications:
- Bachelor's/Master’s degree in Engineering, Economics, Finance, Mathematics, Statistics, Business Administration or a related quantitative field
- 5-7 years of high quality hands-on experience in analytics and data science.
- Strong hands on experience in SQL, Python and one of the AI tools like Claude, Codex, etc
- Use AI tools not just as assistants but as force multipliers,automating repetitive work and scaling insight delivery.
- Have a solid understanding of LLM concepts - embeddings, RAG, and prompt engineering and practical experience applying them in analytics workflows.
- Define the business and product metrics to be evaluated, work with engg on data instrumentation, create and automate self-serve dashboards to present to relevant stakeholders leveraging tools such as Tableau, Qlikview, Looker etc.
- Ability to structure and analyze data leveraging techniques like EDA, Cohort analysis, Funnel analysis and transform them into understandable and actionable recommendations and then communicate them effectively across the organization.
- Hands-on experience in working with large scale structured, semi structured and unstructured data and various approaches to preprocess/cleanse data, dimensionality reduction.
- Work experience in Consumer-tech organizations would be a plus
- Developed a clear understanding of the qualitative and quantitative aspects of the product/strategic initiative and leverage it to identify and act upon existing Gaps and Opportunities
- Hands on experience of A/B testing, Significance testing, supervised and unsupervised ML, Web Analytics and Statistical Learning