Data Analyst with less than a year in Python, SQL, Power BI, and Excel, seeking Data Analyst roles.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Entry-level Data Analyst with hands-on experience in Python, SQL, Power BI, Tableau, and Excel. Completed 3 end-to-end analytics projects involving data cleaning, exploratory data analysis, business KPI reporting, and interactive dashboards. Strong analytical mindset with ability to translate raw data into actionable business recommendations. Actively seeking entry-level Data Analyst or Business Analyst roles.
Uttarakhand Technical University (UTU)
Bachelor of Technology (B.Tech) · Computer Science
August 1, 2022 – June 30, 2026
Swiggy Food Delivery Analytics
January 1, 2026 – June 1, 2026
Analyzed 1,48,442 restaurant records and 4,44,382 delivery records across 552+ Indian cities using Python (Pandas, Seaborn) cleaned raw data, extracted city names from compound strings, removed outliers, and calculated delivery duration from timestamps. Loaded 600K+ rows into SQL Server via SQLAlchemy and wrote 8 business KPI queries — identified peak order hour (2 PM - 69,500 orders), avg delivery time of 31.63 min, and most active rider (Rider #237 - 227 orders). Developed a 5-page interactive Power BI dashboard with Swiggy-orange theme — covering KPI overview, city-level analysis, cuisine trends, delivery operations, and restaurant insights. Business Insight: Delivery time increases significantly beyond 4km — recommended hyperlocal restaurant partnerships and deploying maximum riders during 2-5 PM peak window.
View ProjectHR Employee Attrition Analysis & Prediction
January 1, 2026 – June 1, 2026
Analyzed IBM HR dataset (1,470 employees, 35 features) — discovered overall attrition rate of 16.12%; performed EDA across 6 dimensions: department, salary, age group, overtime, job satisfaction, and tenure. Wrote 8 SQL queries in SSMS 21 for department-wise attrition, salary slab analysis, and identification of top 10 high-risk employees; built ML model (Logistic Regression + Random Forest) to predict churn probability. Published interactive Tableau dashboard with 5 charts showcasing attrition patterns by role, department, and salary range to enable proactive HR decisions. Business Insight: Overtime employees are 3x more likely to leave; Sales dept. has 20% attrition — recommended salary reviews, mentorship for 18-25 age group, and stronger onboarding programs.
View ProjectSuperstore Sales Analytics Dashboard
January 1, 2026 – June 1, 2026
Cleaned 9,994 retail orders (2014-2017) using Python — fixed mixed date formats, derived Order Year/Month/Year-Month columns; built 3 Excel Pivot Tables (Region, Category, Monthly) with XLOOKUP, SUMIF, and COUNTIF formulas. Created Excel KPI dashboard with dynamic charts — Total Sales: $2.30M, Total Profit: $286K, Profit Margin: 12.47%, Loss Orders: 1,871 (18.7%); built 5-page Power BI dashboard with regional treemap and discount-profit scatter analysis. Business Insight: Tables sub-category incurred -$17,725 loss; discounts above 20% consistently caused profit erosion — recommended capping discounts at 15% and discontinuing loss-making sub-categories.
View ProjectData Analyst Bootcamp
Udemy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity (food delivery, HR, retail) suggests adaptability and a broad interest in applying data analysis across different business contexts. The focus on delivering business insights and recommendations aligns well with a results-oriented culture. The self-driven nature of personal projects indicates initiative and a proactive learning attitude.
Soft Skills & Operational Fit
The candidate highlights strong analytical and problem-solving skills, effective communication, documentation, and data storytelling. These are crucial for a Data Analyst role, indicating a good operational fit for roles requiring clear articulation of data insights.