Analytics Specialist

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
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 and data science
• Hands on experience in SQL and Python
• 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 approach to preprocess/cleanse data, dimensionality reduction
• Work experience in Consumer-tech organisations 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

Razorpay believes in and follows an equal employment opportunity policy that doesn't discriminate on gender, religion, sexual orientation, colour, nationality, age, etc. We welcome interests and applications from all groups and communities across the globe.

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