Neha Chothe

Data Analyst

Pune, Maharashtra 0+ yrs exp 86 · Excellent

About

Data Analyst with an MSc in Statistics and hands-on experience building Power BI dashboards, automating reporting workflows, and applying machine learning to real-world datasets. Proficient in Power BI (DAX, Power Query), Excel, SQL, Python, and Tableau. Skilled at translating raw data into clear, actionable insights for marketing and business teams.

Skills & Expertise (20)

Power BI Intermediate

7.0/10

Years Exp

DAX Intermediate

6.5/10

Years Exp

Power Query Intermediate

6.5/10

Years Exp

Cross-Functional Collaboration Intermediate

6.0/10

Years Exp

Business Reporting Intermediate

6.0/10

Years Exp

EDA Intermediate

6.0/10

Years Exp

Data Cleaning Intermediate

6.0/10

Years Exp

SQL Intermediate

6.0/10

Years Exp

Dashboarding Intermediate

6.0/10

Years Exp

Excel Intermediate

6.0/10

Years Exp

Python Intermediate

5.5/10

Years Exp

MySql Intermediate

5.5/10

Years Exp

Pivot Tables Intermediate

5.5/10

Years Exp

XLOOKUP Intermediate

5.5/10

Years Exp

VLOOKUP Intermediate

5.5/10

Years Exp

Tableau Intermediate

5.0/10

Years Exp

scikit-learn Intermediate

5.0/10

Years Exp

Logistic Regression Intermediate

5.0/10

Years Exp

Predictive Modeling Intermediate

5.0/10

Years Exp

Statistical Analysis Intermediate

5.0/10

Years Exp

Work Experience

Data Analyst Intern

Demandify Media

Dec 2025 - May 2026

Built 5+ interactive Power BI dashboards (using DAX and Power Query) to track marketing campaign performance, lead generation, and operational KPIs. Prepared daily, weekly, and monthly performance reports across 3–4 concurrent campaigns to track effectiveness and key business metrics. Analyzed prospect engagement and response trends across campaigns, surfacing insights that supported campaign optimization decisions. Collaborated with marketing and operations teams to monitor trends and identify opportunities for improved outcomes.

Data Science Intern

ScaleUp Analytics

Mar 2025 - Jun 2025

Cleaned and preprocessed a Bank Marketing dataset of 40,000+ client records; conducted EDA to uncover behavioral patterns and campaign response drivers. Built a Logistic Regression model to predict customer campaign response, achieving an ROC-AUC of 0.74. Performed feature analysis and data visualization to identify the key factors influencing campaign outcomes. Documented analytical processes, model results, and recommendations for stakeholder review.