Analytics Specialist

About Razorpay:

Razorpay was founded by Harshil Mathur and Shashank Kumar in 2015. Razorpay is building a new-age digital banking hub (Neobank) for businesses in India. Our mission is to enable frictionless banking and payments experiences for businesses of all shapes and sizes. We started out as a B2B payments company and today, we process billions of dollars of payments for lakhs of businesses across India. We are the leading payments provider in the country and have been the first to bring to market the most major innovations in the past 6 years. Razorpay enables businesses to accept, process, and disburse payments at scale.

Razorpay currently processes multi-billion USD payments on an annualized basis, touching 200Mn+ end customers through top clients like Airtel, Goibibo, Yatra, Ola, Swiggy, Zomato, Cred etc. We architect systems for the scale of not just one segment leader but 1000s put together. With more than a lakh clients, you would have definitely made a payment through Razorpay if you live in India. With the launch of RazorpayX, the company aims to become a leading provider of banking and payout products to businesses covering the gamut of current account, payroll, vendor payouts and many others. Over the past year, the company has disbursed loans worth millions of dollars in loans to thousands of businesses.

The company has raised USD $700M+ in funding till date from marquee investors like GIC, Sequoia Capital, Tiger Global, Ribbit Capital, Matrix Partners and many stellar angels.

The Role:

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.

Roles and 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 hypothesis and validate with sound rigorous methodologies or formulate the problems for modeling with ML
• You would apply excellent problem solving skills and independently scope, deconstruct and formulate solutions from first-principles that bring outside-in and state of the art view
• 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

Mandatory Qualifications:

• Bachelor’s/Master’s degree in Engineering, Economics, Finance, Mathematics, Statistics, Business Administration or a related quantitative field
• 1-3 years of high quality hands-on experience in analytics.
• Hands on experience in SQL and Tableau.
• 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 approach 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
• Working Knowledge of A/B testing, Significance testing, supervised and unsupervised ML, Web Analytics and Statistical Learning