Srinidhi Bhat

Data Scientist

https://talent.gravityer.com/srinidhi-bhat

Exploring ML on GitHub.

Data Science Engineer at Vunet Systems

Key Strengths

Demonstrated experience with Retrieval-Augmented Generation (RAG) and LLM fine-tuning, highly relevant for a Data Scientist role.
Proficiency in Python and Jupyter Notebook, essential tools for data science.
Experience with Computer Vision projects and Class Activation Maps, indicating a breadth of ML knowledge.
Exposure to FastAPI for API development, useful for deploying ML models.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic, showcasing initiative and a strong interest in data science and AI. However, the experience section lists a future start date for a 'Data Science Engineer' role, which is unusual and makes it difficult to assess current professional experience or cultural fit within a team. The project diversity is good within the AI/ML domain, but there's limited evidence of collaborative work or broader business context.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

fastapi-freecodecamp

August 20, 2025 – August 20, 2025

Repo for experimenting with FastAPI. This is a course from Sanjeev Thiyagarajan.

View Project

Coding-Assistant

March 18, 2025 – March 18, 2025

A chatbot that generates, modifies, and explains Python code using qwen2.5-coder-7b-instruct. Built with Gradio for an easy-to-use UI.

View Project

fine-tune-llama-2

November 5, 2023 – November 5, 2023

This project streamlines the fine-tuning process, enabling you to leverage Llama-2's capabilities for your own projects.

View Project

gradio_RAG

August 20, 2023 – August 22, 2023

Code and resources showcasing the Retrieval-Augmented Generation (RAG) technique, a solution for enhancing data freshness in Large Language Models (LLMs). Incorporate up-to-date external knowledge into LLM-generated responses. Additionally, this repository includes a Gradio-based user interface for seamless model deployment.

View Project

AbstractiveQA

April 3, 2023 – April 5, 2023

AbstractiveQA — GitHub repository

View Project

class_activation_maps

January 1, 2022 – January 2, 2022

A Class Activation Map is a weighted activation map generated for each image, helping us to identify the region a CNN is looking at while classifying an image.

View Project

MSOIS

December 1, 2021 – January 29, 2022

Projects from my Masters of Engineering at Manipal School of Information Sciences.

View Project

PGDDS

December 1, 2021 – December 1, 2021

Projects from my PG Diploma in Data Science at Indian Institute of Information Technology - Bangalore

View Project

Computer-Vision-Projects

November 13, 2021 – October 22, 2023

Computer-Vision-Projects — GitHub repository

View Project

External-Internship-Program

May 3, 2019 – June 11, 2022

Colaboratory Python Notebooks for Deep learning projects & Convolution Neural Networks, ordered by Sessions

View Project

Key Strengths

Demonstrated experience with Retrieval-Augmented Generation (RAG) and LLM fine-tuning, highly relevant for a Data Scientist role.
Proficiency in Python and Jupyter Notebook, essential tools for data science.
Experience with Computer Vision projects and Class Activation Maps, indicating a breadth of ML knowledge.
Exposure to FastAPI for API development, useful for deploying ML models.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

Srinidhi Bhat

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit