Operations Analyst

Razorpay is hiring for the role of Operations Analyst!

Responsibilities of the Candidate:

• 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

Requirements:

• 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