Harshita Rani

Software Engineering Intern

Pune, India 0+ yrs exp 76 · Very Good

About

No bio added yet

Skills & Expertise (39)

Generative AI Intermediate

7.6/10

0.5

Years Exp

ML Intermediate

7.6/10

0.5

Years Exp

LLM Intermediate

7.6/10

0.5

Years Exp

NLP Intermediate

7.6/10

0.5

Years Exp

AI Intermediate

7.6/10

0.5

Years Exp

Python Intermediate

7.6/10

0.5

Years Exp

TensorFlow Intermediate

6.4/10

0.5

Years Exp

PyTorch Intermediate

6.4/10

0.5

Years Exp

OpenCV Intermediate

6.4/10

0.5

Years Exp

scikit-learn Intermediate

6.4/10

0.5

Years Exp

Git Intermediate

6.0/10

0.5

Years Exp

Google Colab Intermediate

6.0/10

0.5

Years Exp

Jupyter Notebook Intermediate

6.0/10

0.5

Years Exp

VS Code Intermediate

6.0/10

0.5

Years Exp

GitHub Intermediate

6.0/10

0.5

Years Exp

Pandas Intermediate

6.0/10

0.5

Years Exp

NumPy Intermediate

6.0/10

0.5

Years Exp

Statistics Intermediate

6.0/10

0.5

Years Exp

SQL Intermediate

6.0/10

0.5

Years Exp

LINUX Intermediate

5.2/10

0.5

Years Exp

Matplotlib Intermediate

5.2/10

0.5

Years Exp

Excel Intermediate

5.2/10

0.5

Years Exp

Seaborn Intermediate

5.2/10

0.5

Years Exp

MySql Intermediate

5.2/10

0.5

Years Exp

MongoDb Intermediate

5.2/10

0.5

Years Exp

PowerBI Beginner

4.0/10

0.5

Years Exp

Computer Networks Beginner

4.0/10

0.5

Years Exp

OS Beginner

4.0/10

0.5

Years Exp

DBMS Beginner

4.0/10

0.5

Years Exp

OOP Beginner

4.0/10

0.5

Years Exp

Algorithms Beginner

4.0/10

0.5

Years Exp

Data Structures Beginner

4.0/10

0.5

Years Exp

Canva Beginner

4.0/10

0.5

Years Exp

Figma Beginner

4.0/10

0.5

Years Exp

RStudio Beginner

4.0/10

0.5

Years Exp

CSS Beginner

4.0/10

0.5

Years Exp

HTML Beginner

4.0/10

0.5

Years Exp

JavaScript Beginner

4.0/10

0.5

Years Exp

C++ Beginner

4.0/10

0.5

Years Exp

Work Experience

Software Engineering Intern

Emergeflow Technologies

Jan 2026 - Jun 2026

Engineered an automated Python data pipeline processing SEC filings and CRSP market data for 28,700+ companies, using NLP semantic search to extract 93,000+ risk exposures and reducing preprocessing time by 80%. Constructed machine learning models (Random Forest, OLS) on a 93,000+ record dataset with outlier removal, improving volatility prediction accuracy by 15% and identifying key risk indicators with 95% confidence. Devised Generative AI workflows using diffusion models and CV techniques, reducing manual product photography effort by 60%.