Nvidia Data Insights Analytics Engineer 

India, Maharashtra, Pune 

105773564

What you'll be doing:

• Design and develop comprehensive analytics solutions and interactive dashboards for subscription metrics, payment performance, fraud patterns, and revenue optimization

• Build robust reporting frameworks with scalable solutions and customizable templates for internal and external stakeholders

• Develop payment analytics, fraud detection models, chargeback analysis frameworks, and revenue leakage detection systems

• Transform complex data into compelling narratives through executive-level presentations and self-service documentation

• Create attribution analytics, customer segmentation models, and lifecycle analytics to optimize marketing investments

• Collaborate with cross-functional stakeholders to translate business questions into technical analytics requirements

• Research and implement advanced analytics techniques while staying current with industry trends

• Establish data validation frameworks and monitoring systems to ensure the accuracy of financial and behavioral metrics

What we want to see:

• Bachelor's degree in Data Science, Statistics, Business Analytics, or related field

• 5+ years of experience in data analytics with exposure to commerce, payments, or subscription businesses

• Proficiency with Apache Spark and Databricks for large-scale data transformation, analysis, and developing production-ready notebook workflows

• Strong proficiency in SQL and data analysis programming languages (Python, R)

• Experience with business intelligence and visualization tools (AWS Quicksight, Tableau, Power BI, Looker)

• Knowledge of financial metrics, payment KPIs, and risk indicators

• Experience translating complex transactional data into business insights

• Background in developing dashboards for different audiences with varying technical sophistication

• Understanding of fraud analytics, payment performance metrics, or revenue optimization techniques

Ways to stand out from the crowd:

• Master's degree in a relevant field

• Experience with commerce platforms, payment processors, or fraud prevention systems

• Background in marketing analytics, customer segmentation, or lifetime value modeling

• Knowledge of machine learning techniques for anomaly detection or predictive analytics

• Experience with financial reporting, revenue forecasting, or business performance analysis