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Data Science with less than a year in Python, SQL & Power BI.
Completed 20+ technical assessments in SQL, Python (Pandas, NumPy), Power BI, and Excel, demonstrating hands-on proficiency across the core data analytics toolkit. Executed exploratory data analysis (EDA) on structured training datasets using Python (Pandas, NumPy), identifying data patterns, handling null values, and summarizing statistical distributions. Wrote SQL queries daily covering joins, aggregations, filters, and subqueries to extract, transform, and summarize structured data across relational datasets. Analyzed a sports dataset of 756+ records using Python (Pandas, Matplotlib), uncovering a win-rate pattern where batting-first teams won 66.7% of matches compared to 33.3% for bowl-first teams. Developed an interactive Power BI dashboard visualizing revenue and profit by product categories and subcategories, enabling faster identification of high-performing segments and cutting manual reporting effort.
International Centre of Excellence in Engineering and Management
Bachelor of Engineering · Electrical and Electronics
December 1, 2021 – August 1, 2025
The Sparks Foundation
Data Science & Business Analytics Intern
February 1, 2023 – March 1, 2023
India
AlmaBetter
Data Science Trainee
October 1, 2022 – April 1, 2023
India
End-to-End Retail Sales Analytics
June 1, 2026 – Present
Built an end-to-end Bronze, Silver, Gold data pipeline in Microsoft Fabric using Python (Pandas) and Spark, processing 9,000+ retail records and storing cleaned output as Delta tables in a Lakehouse. Engineered a star schema semantic model in Microsoft Fabric using DataFlow Gen2, and wrote 10+ SQL queries with CTEs, subqueries, and window functions via the SQL Analytics Endpoint for dimensional retail analysis. Deployed a Power BI dashboard with 10+ DAX KPIs covering profitability, shipping, and customer insights surfacing West as the top revenue region at $107K and Office Supplies as the highest loss category at 884 loss orders.
View ProjectWalmart Sales Dashboard
June 1, 2026 – Present
Built an interactive Power BI sales dashboard covering 4 years of Walmart performance totaling $725.46K in revenue, with year-over-year profit comparison from $140K (2012) to a peak of $251K (2014). Segmented category-level sales data in Power BI, identifying Phones as the highest-selling category at 35% of total sales and Binders as the most profitable at $16.10K profit. Tracked monthly revenue and profit trends, surfacing December as both the highest-selling and most profitable month with $13.26K profit.
Microsoft Certified: Fabric Analytics Engineer Associate
Microsoft
June 1, 2026 – Present
Full Stack Data Science Certification
AlmaBetter
June 1, 2026 – Present
Google Data Analytics Professional Certificate
Google (Coursera)
June 1, 2026 – Present
Problem-Solving Achievement
HackerRank
June 1, 2026 – Present
SQL 50 study plan
LeetCode
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects and certifications show a strong focus on data analytics and data science, aligning well with a Data Science target role. The diversity of tools and platforms (Microsoft Fabric, AWS, GCP, Power BI, Python, SQL) indicates a willingness to learn and adapt to various technical environments. However, the experience is primarily academic and internship-based, which might require additional mentorship in a fast-paced corporate environment.
Soft Skills & Operational Fit
The candidate demonstrates an ability to work on structured projects and apply analytical criteria, as seen in peer project evaluations. The project descriptions indicate a results-oriented approach, focusing on identifying key insights and business impact. However, the short duration of internships and lack of team-based project descriptions limit the assessment of collaboration and stress handling.