Disha Naveen

Data Analyst Intern

Bhopal, Madhya Pradesh 0+ yrs exp 80 · Excellent

About

Analytical Computer Science graduate (2026) with a strong foundation in statistics, probability, and machine learning, and hands-on experience in SQL, Python, and Power BI. Skilled in root-cause analysis, anomaly/outlier detection, and building predictive models and performance dashboards that drive fast, data-backed business decisions. Comfortable working with large datasets across cross-functional teams to turn ambiguous business problems into clear analytical solutions.

Skills & Expertise (32)

Excel Advanced

8.0/10

Years Exp

SQL Intermediate

7.5/10

Years Exp

Python Intermediate

7.0/10

Years Exp

Data Cleaning Intermediate

7.0/10

Years Exp

Statistical Analysis Intermediate

6.5/10

Years Exp

Pandas Intermediate

6.5/10

Years Exp

NumPy Intermediate

6.5/10

Years Exp

Root-cause analysis Intermediate

6.0/10

Years Exp

Power BI Intermediate

6.0/10

Years Exp

EDA Intermediate

6.0/10

Years Exp

Machine Learning Beginner

5.5/10

Anomaly Detection Beginner

5.5/10

Git Beginner

5.5/10

Model Evaluation Beginner

5.0/10

Classification Models Beginner

5.0/10

SQLite3 Beginner

5.0/10

DAX Beginner

5.0/10

SciPy Beginner

4.5/10

TensorFlow Beginner

4.5/10

scikit-learn Beginner

4.5/10

PyTorch Beginner

4.5/10

OpenCV Beginner

4.5/10

YOLOv5 Beginner

4.5/10

SQLAlchemy Seaborn Cross-Functional Communication Technical Documentation AWS Probability Matplotlib Data Modeling Linear Algebra

Work Experience

Data Analyst Intern

Bluestock Fintech

Jun 2026 - Jul 2026

Cleaned and validated 11,000+ data points across 92 companies and 12 datasets, applying 14 data-quality rules to catch anomalies and ensure accurate reporting. Wrote SQL queries and computed 50+ financial KPIs to support a multi-filter screener and sector/peer benchmarking, validated to ±2% accuracy against manual checks. Translated raw financial data into automated Excel/PDF reports and an interactive dashboard, making insights accessible to non-technical stakeholders.