Pratik Savadi

Professional experience of 8 years with a strong background in Python, Machine learning, Deep learning, data analytics and NLP. With experience in developing predictive models and working on various data science tools, I am eager to explore data sets to solve complex business problems. Strong communication skills with the ability to effectively translate complex technical concepts to non-technical stakeholders. Having knowledge in all stages of the data science lifecycle, from data collection and preprocessing to model deployment and visualization.

Role
Senior Associate & Robotics engineer
Years of Experience
7.60 years
Professional Portfolio
View here

Skillsets

Python - 5.0 Years
SQL - 2 Years
rag - 3 Years
API - 2 Years
LLMs - 3 Years
Communication - 4 Years
ML - 4 Years
predictive models - 3 Years
Hugging Face - 2 Years
Generative AI - 3.0 Years
LangChain - 2.0 Years
LLAMA - 2.0 Years
TensorFlow - 03 Years
PyTorch - 4.0 Years
AWS - 02 Years
pandas
NLP - 03 Years
MLOps - 2.0 Years
LLM - 02 Years
Kubernetes
Kubernetes
Git
Git
Gen AI
Docker - 2 Years
Deep Learning - 4.0 Years
AWS

Professional Summary

7.60Years

Jan, 2022 - Present4 yr 2 months
Senior Associate
Definitive Healthcare
Jan, 2018 - Dec, 20213 yr 11 months
Data Analyst/Software Engineer
AlgoFusion Technologies
Jan, 2016 - Dec, 20171 yr 11 months
Robotics Engineer
Mahajan Automation

Applications & Tools Known

Pycharm
Python
Pandas
Machine Learning
Deep Learning
Tensorflow
MLFLOW
AWS
S3
AWS IAM
Neural Networks
LangChain
VS Code
MongoDB
PowerBI

Work History

7.60Years

Senior Associate

Definitive Healthcare

Jan, 2022 - Present4 yr 2 months

Developed a machine learning model to identify the Next Best Action (NBA) for increasing sales. Utilized data-driven insights and analytics to predict accurate content and offers for consumers. Developed and deployed a machine learning model Next Best Action (NBA), leveraging MLflow for experiment tracking and model management on an AWS EC2 instance. Developed a question-answering chatbot using PyTorch, NLP techniques, neural networks, and ChromaDB for vector storage. Developed a question-answering chatbot using local Large Language Models (LLMs) like Ollama, the LangChain framework, and AstraDB for vector storage. Create a Lambda function that identifies EBS snapshots that are no longer associated with any active EC2 instance and deletes them to save on storage costs.

Data Analyst/Software Engineer

AlgoFusion Technologies

Jan, 2018 - Dec, 20213 yr 11 months

It's an enterprise product for automated reconciliation process of different types of money transactions like NEFT, RTGS, IMPS, BBPS, INTERNET BANKING and so on in bank as well as stock market which will validate the number of transactions are matched or unmatched on the bank side as well as user side.

Robotics Engineer

Mahajan Automation

Jan, 2016 - Dec, 20171 yr 11 months

A company focused on engineering automation solutions. Engaged in robotics engineering projects focused on automation processes.

Major Projects

3Projects

RAG-Doc-Q-A-with-GROQ-API-and-HuggingFace-Embeddings

Jan, 2025 - Jan, 2025

Developed a Retrieval Augmented Generation (RAG) based document question-answering system using the GROQ API for querying a document store and Hugging Face embeddings for semantic search.

Blog-Generation-using-AWS-LAMBDA-and-AWS-BEDROCK

Dec, 2024 - Dec, 2024

The Lambda function takes the input from user to generate blog. It also calls the relevant LLM model from AWS BEDROCK. It also calls the S3 bucket where the blog is stored as text file. Then we created the API using AWS API GATEWAY where the lambda function is integrated. The API is called it from POSTMAN APP where blog topic is also given as input.

ML-Project-using-AWS-SAGEMAKER