Data Analyst with 3+ years in SQL, Python, and Statistical Modeling
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Results-driven Data Analyst with 3+ years of experience in SQL, Python, statistical analysis, ETL validation, and business intelligence reporting. Experienced in applying statistical techniques to large-scale datasets, building regression and forecasting models, developing interactive KPI dashboards, and conducting exploratory data analysis (EDA) to support data-driven decision-making. Proficient in identifying patterns and trends in complex datasets, designing reporting infrastructure, and collaborating with cross-functional stakeholders to deliver actionable insights and improve operational efficiency.
Scaler Academy
Advanced Certificate · Data Science & Machine Learning (Regression, Classification, Clustering)
August 1, 2026 – Present
University Institute of Engineering & Technology (UIET), MDU
Bachelor of Technology · Electronics & Communication Engineering
August 1, 2018 – June 30, 2022
HCLTech
Data Analyst
August 1, 2022 – Present
India
Interactive Super Store Sales Dashboard
January 1, 2021 – January 1, 2022
• Designed an interactive Tableau dashboard analyzing $12.6M+ in Sales, $1.46M+ Profit, and 178K+ Units Sold with dynamic KPI scorecards and trend visualizations. • Implemented parameter-driven filters for State, Category, Sub-Category, and Ship Mode, enabling self-service analytics and drill-down business intelligence reporting. • Applied calculated fields, dashboard actions, and visualization best practices to deliver a production-ready BI reporting solution that directly supports data-driven business decision-making.
Airline Loyalty Program YoY Analysis & Predictive Modeling
January 1, 2019 – January 1, 2021
• Designed relational database schemas and end-to-end analytical models to evaluate customer flight activity and loyalty histories across thousands of program members. • Developed advanced SQL queries with CTEs and pivoted time-series models to track YoY growth in flights and point accumulations across loyalty tiers (Star, Nova, Aurora). • Built supervised classification models using scikit-learn to predict customer churn risk across loyalty tiers, benchmarking promo-driven enrollments against standard acquisition methods to measure campaign ROI. • Derived key metrics — monthly flights, redemption rates, and point accumulation patterns — enabling data-driven portfolio decisions and process improvement recommendations.
View ProjectTarget Brazil E-Commerce Portfolio Performance Analysis
January 1, 2017 – January 1, 2018
• Performed end-to-end EDA on large-scale e-commerce datasets spanning 29 Brazilian states and 4,000+ cities to uncover customer behavior, logistics trends, and portfolio-level performance patterns. • Developed regression models using historical order data to forecast revenue trends and freight cost trajectories, surfacing actionable business growth drivers for stakeholder reporting. • Applied segmentation techniques to classify customer cohorts by purchasing behavior, enabling targeted business analysis across regional and product-level dimensions. • Identified a 136.97% increase in total order value (2017-2018) through statistical trend analysis and built interactive Tableau dashboards with dynamic KPI filters to communicate insights effectively.
Cultural Fit Analysis
The candidate's project diversity, ranging from e-commerce performance analysis to airline loyalty programs, indicates adaptability and a broad interest in applying data analysis across different domains. Their current role as a Data Analyst at HCLTech aligns well with the target role, suggesting a good cultural fit for a data-centric organization that values analytical rigor and practical application of data science techniques.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical thinking, problem-solving skills, and attention to detail through their work in data validation, RCA, and identifying business growth opportunities. Their experience in collaborating with cross-functional teams and managing stakeholder expectations indicates good operational fit and communication skills for a data-driven environment.