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Data Analyst with less than a year in SQL, Python, and Power BI, experienced in data cleaning, analy
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Detail-oriented professional skilled in SQL, Python, and Power BI, with experience in data cleaning, analysis, and visualization. Developed dashboards and metrics that supported data-driven decision-making in market and safety projects. Able to turn complex data into clear insights that improve efficiency and support business growth.
Chandigarh University
Master of Computer Applications (MCA)
August 1, 2023 – July 1, 2025
Lucknow University
Bachelor Of Commerce (B.Com)
August 1, 2020 – June 1, 2023
EV Market Analysis
June 28, 2026 – Present
Evaluated three years of EV sales data (FY 2022-2024) to guide market expansion for a US-based automotive leader with less than 2% market share. Constructed complex SQL queries using CTEs and Window Functions to calculate key metrics, including Compound Annual Growth Rate (CAGR) and market penetration for top manufacturers. Designed an interactive Power BI dashboard to track quarterly trends, identifying seasonal patterns and projecting sales volumes for 2030 across the top 10 states. Formulated strategic recommendations, pinpointing Tamil Nadu and Maharashtra as the best manufacturing hubs based on government subsidies and infrastructure analysis.
Road Accident Analysis
June 28, 2026 – Present
Examined a dataset of over 417,000 records to uncover trends in road accident casualties over a three-year timeline (2021-2023). Built a dynamic dashboard tracking four Key Performance Indicators (KPIs), revealing a 1.7% fatality rate and 14.2% serious injury rate to highlight critical safety areas. Categorized incidents by vehicle type, determining that private cars were the main cause of casualties (79.8%), followed by commercial vans and bikes. Assessed environmental factors, finding that 73% of accidents occurred during daylight and identifying Single Carriageways as the highest-risk road type (309k+ casualties).
Grocery Sales Analysis
June 28, 2026 – Present
Processed 8,500+ transaction records to check sales performance, customer satisfaction, and inventory distribution for a quick-commerce platform. Executed rigorous data cleaning in Python (Pandas) to fix inconsistent categories, achieving 100% data uniformity. Uncovered that Tier 3 locations performed better than Tier 1 and Tier 2 cities, generating ₹472k (approx. 39% of total revenue). Classified product performance by fat content and found that Regular Fat items (₹776k) significantly outperformed Low Fat products (₹425k), despite prevailing health-focused market trends.
Python
Coursera
June 1, 2026 – Present
Data Analytics
Coursera
June 1, 2026 – Present
Data Science
Growing Seed Tech
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects show a diverse application of data analysis across different domains (automotive, road safety, e-commerce), indicating adaptability and a broad interest in leveraging data. The focus on practical, business-oriented outcomes in their projects aligns well with a results-driven culture. The pursuit of a Master's degree in Computer Applications while having a Bachelor's in Commerce suggests a proactive approach to skill development and a strong drive for career growth, which is a positive cultural indicator. However, the lack of professional experience means their ability to navigate corporate culture and team dynamics is unproven.
Soft Skills & Operational Fit
The candidate demonstrates strong analytical and problem-solving skills through their project work, particularly in identifying trends and formulating strategic recommendations. Their ability to translate complex data into clear insights is a valuable operational fit for a Data Analyst role. However, without specific assessment data on communication or teamwork, it's difficult to fully assess soft skills like collaboration or stress handling.