Mukesh Samrit

Aspiring Data Analyst

Gondia, Maharashtra 0+ yrs exp 82 · Excellent

About

Entry-level Data Analyst with B.E in Civil Engineering and hands-on experience in churn prediction, salary forecasting, retail sales, and warehouse logistics analytics. Strong SQL (HackerRank & Datacamp-certified), Excel, Power query and Python skills, with practical use of Power BI and Tableau to build dashboards that explain key business drivers and support decision-making.

Skills & Expertise (66)

Data Cleaning Intermediate

8.5/10

0.5

Years Exp

Exploratory data analysis Intermediate

8.5/10

0.5

Years Exp

Python for Data Analysis Advanced

8.4/10

Years Exp

Pandas Intermediate

8.0/10

0.5

Years Exp

Python Intermediate

8.0/10

0.5

Years Exp

SQL Intermediate

8.0/10

0.5

Years Exp

Google Sheets Intermediate

7.5/10

0.5

Years Exp

MySql Intermediate

7.5/10

0.5

Years Exp

Excel Intermediate

7.5/10

Years Exp

NumPy Intermediate

7.0/10

0.5

Years Exp

Basic Statistics Intermediate

7.0/10

0.5

Years Exp

Matplotlib Intermediate

7.0/10

0.5

Years Exp

Tableau Beginner

6.0/10

0.5

Years Exp

Power BI Beginner

6.0/10

0.5

Years Exp

Index-match XLOOKUP lookup formulas PivotTables ETL Fundamentals Relational Database Filtering Conditional Formatting Attention to Detail Business Insights stakeholder communication Requirements Gathering Documentation Verification Trend Analysis Problem Solving Communication Sorting Data Storytelling KPI Reporting Basic Predictive Modeling Feature Engineering Reporting Excel Macros Power Query ELT Pivot Tables Complex Joins GROUP BY HAVING Subqueries Window Functions RANK ROW_NUMBER Lead LAG CTEs Query Optimization VLOOKUP Data Validation MS Word PowerPoint Dashboard Design Data Modeling Interactive Reporting EDA Seaborn Database Fundamentals ETL Concepts SQL Queries Aggregations CASE Statements

Work Experience

Data Analytics & AI Virtual Intern

IBM SkillsBuild (via AICTE / Edunet Foundation–CSRBOX)

Jan 2026 - Present

Cleaned and validated a customer churn dataset (2,001 orders, 416 customers) using Google sheet, SQL, and Python using Google gemini. Performed EDA and built dashboards to visualize churn drivers, customer segments, and key risk indicators. Developed a churn prediction model in Google Colab (Python, Gemini) achieving 98.8% accuracy and 100% recall.