Data Analyst Analytics

Mohini Anil Somvanshi

845-***-**** *******************@*****.*** Pune, Maharashtra

www.linkedin.com/in/mohini-somvanshi-437a11343

Professional Summary

Results-driven Data Analyst with proven experience translating complex business questions into actionable insights. Highly proficient in SQL (including complex joins, window functions, and CTEs) and skilled in Python (Pandas, NumPy) for advanced data manipulation. Adept at designing intuitive, impactful dashboards using Power BI to support data-driven decision-making. Known for clear communication of technical insights to both technical and non-technical audiences. Passionate about solving business challenges with data and leveraging modern tools, including LLMs (e.g., ChatGPT, Copilot), to optimize analytical workflows and innovate problem-solving approaches.

Education

B.Sc., B.D. Kale Mahavidyalaya Ghodegaon, Savitribai Phule Pune University – 2020 (74.40%)

Certification in Data Analytics, [Edutech Warje], Pune – 2025

Technical Skills

Programming: Python (Pandas, NumPy, Matplotlib, Seaborn), SQL

Data Visualization: Power BI, Tableau (basic)

Tools: Excel (Pivot Tables, VLOOKUP, Charts), Power Query, DAX

Techniques: Data Cleaning, Exploratory Data Analysis (EDA), Customer Segmentation, Trend Analysis

Other Tools: Jupyter Notebook

Internship

Data Analyst Intern Wayzon Technology, Pune

March 2025 – September 2025

Built and maintained dashboards in Power BI to track KPIs.

Wrote SQL queries and Python scripts for data cleaning, transformation, and reporting.

Conducted EDA to identify customer and business trends, improving reporting accuracy.

Collaborated with senior analysts to deliver insights for client decision-making.

Projects

Diwali Sales Analysis Project Remote (2024) – Data Analyst (Python & Retail Domain)

Analyzed 11,251 customer records to uncover sales and demographic insights.

Performed data cleaning (handled null values, dropped unnecessary columns).

Identified top states (Uttar Pradesh, Maharashtra, Karnataka) and high-performing zones (West & South).

Found that 26–35 yrs married women in IT, Healthcare, and Aviation sectors were key buyers.

Discovered top product categories: Clothing (23.6%), Food (22.1%), Electronics & Gadgets (18.5%).

Built visualizations using Python (Matplotlib, Seaborn) to show customer trends.

Suggested business strategies: targeted campaigns, inventory planning, bundling offers, and loyalty programs.

Strengths

Strong Analytical Thinking

Quick Learner

Team Collaboration

Attention to Detail

Additional Information

Languages: English (Fluent), Hindi (Fluent), Marathi (Fluent)

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