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Data Scientist with 1+ years in Python, SQL & Machine Learning
Data Analyst with a foundation in Mathematics and hands-on experience in Python, SQL, Power BI, Tableau, and Statistical Modelling. Experienced in data wrangling, exploratory data analysis (EDA), predictive modelling, data validation, and dashboard creation across structured and unstructured datasets. Skilled in translating complex data into actionable, client-ready insights through rigorous analysis, KPI reporting, and data-driven storytelling. Committed to delivering quality analytical work, maintaining data integrity, and supporting informed business decisions in collaborative, fast-paced environments. Demonstrates a strong learning mindset, intellectual curiosity, effective communication, and stakeholder-focused problem-solving while taking ownership of analytical deliverables and continuous professional development.
Brototype, Bengaluru
Data Science Bootcamp
August 1, 2023 – June 30, 2024
Amrita Vishwa Vidyapeetham, Coimbatore
BSc · Mathematics
August 1, 2017 – June 30, 2020
Upgrad School of Technology (formerly Aimerz.ai)
Data Scientist
September 1, 2025 – December 1, 2025
India
Aimerz.ai
Data Science Content Strategist Associate
August 1, 2024 – September 1, 2025
India
BCGX Project - Customer Churn Prediction & Retention Strategy
June 1, 2025 – June 1, 2026
Conducted end-to-end customer behavior and attrition analysis on 14,600+ customer accounts to identify churn drivers, segment high-risk customers, and develop targeted retention strategies. Performed data cleaning, feature engineering, and statistical analysis, creating 15+ business-driven features including pricing, tenure, and customer activity metrics. Developed and evaluated a Random Forest classification model achieving 90.3% accuracy and 78.3% precision across validation datasets. Conducted exploratory data analysis using Matplotlib and Seaborn to uncover churn trends, customer behavior patterns, and business insights. Translated model outputs into actionable retention strategies, identifying 23 high-risk customer segments and recommending targeted interventions to improve customer retention, customer lifetime value, and overall business outcomes.
View ProjectIPL Analysis Dashboard Using Tableau
June 1, 2025 – June 1, 2026
Analyzed IPL match and player datasets to identify performance trends, track KPIs, and generate actionable insights through interactive Tableau dashboards. Developed KPI scorecards, trend reports, and performance breakdown dashboards using data cleaning, transformation, and aggregation techniques. Enabled stakeholder-driven exploration of team and player metrics through interactive reporting and filtering capabilities.
Bike Taxi Ride Request Demand Forecast
June 1, 2025 – June 1, 2026
Engineered an end-to-end forecasting pipeline processing 8.38 million ride records, applying data cleaning, validation, and feature engineering techniques. Developed a structured forecasting dataset containing 878,400 observations across 50 geographic demand zones. Conducted statistical analysis using ACF and PACF to identify temporal dependencies and support lag-based feature engineering. Evaluated Linear Regression, Random Forest, and XGBoost models, selecting XGBoost based on superior generalization performance and achieving RMSE 0.84. Deployed a recursive forecasting pipeline to generate future demand predictions and support operational planning decisions.
View ProjectCultural Fit Analysis
The candidate's project diversity, ranging from customer churn prediction to demand forecasting and dashboard creation, indicates a broad interest in applying data science across different domains. The experience in both a Data Scientist and Data Science Content Strategist Associate role, coupled with a Data Science Bootcamp, shows a commitment to the field. The listed collaboration skills (Stakeholder Management, Cross-functional Collaboration, Teamwork) suggest a good fit for a collaborative work environment. The target role 'Data Scientist' aligns well with the candidate's experience and stated skills.
Soft Skills & Operational Fit
The candidate's resume highlights strong communication, stakeholder management, and teamwork skills, which are crucial for a Data Scientist role. The emphasis on translating model outputs into actionable strategies and partnering with business teams indicates a good operational fit. The mention of a 'strong learning mindset' and 'intellectual curiosity' suggests a proactive approach to professional development.