Anuj Jagtap

Data Analyst

Pune, Maharashtra, India 0+ yrs exp 81 · Excellent

About

M.Sc. Statistics graduate and Data & Business Analyst Intern with hands-on experience across the full analytics lifecycle — large-scale data collection, cleaning, and validation, advanced SQL, Python-based machine learning, and Power BI dashboards that turn complex data into clear business recommendations. Led a live company data project handling 43,000+ records end-to-end, and built an advanced ML platform (XGBoost, SHAP, Streamlit) that predicts career outcomes from a 2,750-candidate, 37-feature dataset. Backed by dedicated SQL, Python, and ML practice, a strong statistical foundation, and practical GenAI exposure (LLMs, RAG, prompt engineering). Detail-oriented, quick to learn, and skilled at presenting insights to both technical and non-technical stakeholders.

Skills & Expertise (61)

Pandas Advanced

8.5/10

0.5

Years Exp

SQL Server Advanced

8.0/10

0.5

Years Exp

Data Storytelling Advanced

8.0/10

0.5

Years Exp

Statistical Modeling Advanced

8.0/10

0.5

Years Exp

Hypothesis Testing Tableau Power Query DAX Power BI Predictive Analytics Model Evaluation Probability SARIMA ARIMA Time-Series Forecasting SHAP Clustering Advanced Excel Pivot Tables XLOOKUP VLOOKUP Index-match SUMIFS Web Scraping Data Cleaning Transformation LLMs Retrieval-Augmented Generation Prompt Engineering ChatGPT Claude Gemini Data Validation KPI Tracking Trend & Anomaly Analysis Business Insights Dashboards & Reporting Joins Subqueries CTEs Window Functions ROW_NUMBER RANK LAG Lead GROUP BY HAVING Cross-Validation NumPy Matplotlib Seaborn scikit-learn XGBoost Streamlit Jupyter Notebook Git GitHub Regression Classification EDA Feature Engineering

Work Experience

Data & Business Analyst Intern

Analytics Career Connect

Jun 2026 - Present

Led a live market data collection project — scraped 43,000+ raw company records, overcame real website security and anti-scraping obstacles, validated the dataset down to 41,500+ accurate records, and delivered the dataset and an interactive Streamlit dashboard end-to-end. Collect, clean, and transform large, multi-source datasets using Python, SQL, and Excel, ensuring accuracy and consistency before analysis. Run exploratory data analysis and apply statistical and machine learning techniques to identify trends and generate predictive, business-ready insights. Build and maintain interactive Power BI dashboards and recurring reports tracking KPIs for stakeholders. Translate business questions into clear analyses and present findings to technical and non-technical audiences. Use AI tools such as ChatGPT and Claude to accelerate research and documentation, independently verifying outputs.