Meghana M

Aspiring Data Research Analyst

Bengaluru, India 80 · Excellent

About

Detail-oriented, hypothesis-driven graduate (Bachelor of Computer Applications, 2026) with hands-on experience querying, cleaning, and analysing large datasets to answer research questions and surface actionable patterns. Proficient in SQL, Python, and Advanced Excel, with practical experience building metrics, KPIs, and dashboards using Power BI to support day-to-day business decisions. Comfortable running exploratory analysis to test hypotheses, and translating raw data into clear, decision-ready findings. Strong written and spoken English, with a track record of independently completing data projects to full delivery.

Skills & Expertise (28)

scikit-learn Intermediate

7.6/10

Years Exp

Team Collaboration Intermediate

7.6/10

Years Exp

Time management Intermediate

7.6/10

Years Exp

Problem Solving Intermediate

7.6/10

Years Exp

Clear Communication Intermediate

7.6/10

Years Exp

Attention to Detail Intermediate

7.6/10

Years Exp

Analytical Thinking Intermediate

7.6/10

Years Exp

Data Analysis Intermediate

7.6/10

Years Exp

Machine Learning Intermediate

7.6/10

Years Exp

Data Science Intermediate

7.6/10

Years Exp

Python Intermediate

7.6/10

Years Exp

Exploratory data analysis Intermediate

7.6/10

Years Exp

Data Cleaning Intermediate

7.6/10

Years Exp

Hypothesis Testing Intermediate

7.6/10

Years Exp

Pandas Intermediate

7.1/10

Years Exp

NumPy Intermediate

7.1/10

Years Exp

SQL Intermediate

7.1/10

Years Exp

MySql Intermediate

6.1/10

Years Exp

Advanced Excel Intermediate

6.1/10

Years Exp

Git Beginner

5.6/10

Power BI Beginner

5.6/10

Natural Language Processing Beginner

5.6/10

DAX Beginner

4.1/10

PhpMyAdmin Beginner

4.1/10

Flask Beginner

4.1/10

CSS Beginner

4.1/10

HTML Beginner

4.1/10

Java Beginner

3.6/10

Work Experience

Data Science Intern

Prinston Smart Engineers

Jan 2025 - Jan 2025

Queried, cleaned, and analysed large raw datasets, handling missing values and structuring data to answer a defined research question about key factors driving student depression. Ran exploratory data analysis and applied statistical models (Logistic Regression, Random Forest, SVM) to test hypotheses and surface meaningful patterns in the data. Evaluated model performance using data analysis techniques, translating complex findings into clear, decision-ready insights for the team. Collaborated within a professional team setting, applying structured, hypothesis-driven analytical workflows from question to result.