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Data Analyst with 2+ years in product analytics, SQL, Python, and A/B testing.
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Assessing your cultural and operational fit
Data Analyst with 2+ years at Jio Platforms delivering product analytics for a 10M+ user application. Proficient in SQL, Python, and Amazon Redshift with hands-on expertise in DAU/MAU tracking, churn analysis, retention analysis, funnel analysis, A/B testing, and statistical analysis. Delivered a ~40% improvement in feature completion rates through hypothesis-driven, data-backed product decisions in close collaboration with Product and Engineering teams.
MGM's College of Engineering, Nanded
B.Tech · Computer Science and Engineering
August 1, 2019 – June 30, 2023
Jio Platforms Limited
Data Analyst
January 1, 2024 – Present
India
TEAM PERFORMANCE DASHBOARD
June 24, 2026 – Present
Designed and built a cross-functional KPI tracking dashboard to monitor team-specific performance metrics – bugs raised and resolved for QA, delivery timelines for Engineering, and task turnaround time for Operations. Wrote SQL pipelines to extract, clean, and aggregate data from multiple sources into a unified reporting layer; replaced manual Excel-based reporting with a self-serve Power BI dashboard for all team leads. Collaborated with stakeholders across QA, Engineering, and Operations to define team-specific KPI definitions and deliver consistent, comparable metrics on a single consolidated dashboard.
Cultural Fit Analysis
The candidate's experience at Jio Platforms Limited, a large-scale technology company, suggests an ability to work in dynamic, fast-paced environments. Their involvement in cross-functional projects and stakeholder collaboration indicates a team-oriented approach. The diversity of analytical tasks (product, chatbot, team performance) shows adaptability and a broad interest in applying data skills across different business functions, aligning well with a data analyst role that often requires engaging with various departments.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving through data, and effective collaboration with diverse stakeholders. Their experience in defining KPIs and translating business requirements into technical solutions indicates good operational fit for a data-driven environment. The project descriptions highlight initiative and ownership in delivering self-serve reporting solutions.