AI Engineer or Data Scientist

12/2023 – 5/2024

1) Developed and streamlined PDF processing tasks by creating multiple FASTAPI endpoints using the LangChain framework
2) Implemented RAG-based approach for question answering and PDF comparison tasks, and fine-tuned LLMs to support AP business unit operations
3) Developed time series prediction models for company’s own python library using Azure ML Studio that enables regional teams to create country-specific models
4) Automated deployment of SGI library to Azure DevOps artifacts to ensure easy integration with DataBricks notebooks
5) Conducted thorough Data Analysis and EDA for multiple crop systems and financial KPIs (Gross Margin, Net Sales, Market Share) to support business operations and decision-making
6) Performed EDA to understand the nature of the master data and evaluate predictions from different time series models, analyzing KPIs such as Net Promotor Score (NPS), and Customer Acquisition Costs (CAC)
7)Enhanced the chatbot’s capability using conversational retrieval chains, agents, and tools to provide instant page-specific answers

Data Science

6/2023 – 11/2023

1) Enhanced the platform’s strategic charging point planning capabilities through ML end-to-end solutions, leveraging tools such as, NumPy, Pandas and Scikit-Learn
2) Used models like MLP, LSTM, Gradient boosting, Random Forest, and oversampling technique (SMOTE) to perform location analysis
3) Automated data scraping procedures using BeautifulSoap, enhancing data acquisition accuracy
4) Developed a Streamlit-powered application for comprehensive performance assessment of diverse ML models

Data Science

6/2022 – 4/2023

1) Led the end-to-end development of a pipeline for optimal cloud provider selection based on application requirements using ML based solution.
2) Built a pipeline to provision virtual machines on AWS, Azure and GCP using the IaC tool Terraform and developed a centralized platform with Infracost to compare costs across cloud providers.
3) Built a web dashboard using Tableau, Plotly, and Dash to monitor real-time resource utilization and implemented an LSTM model for forecasting CPU, HDD, and RAM usage.

Data Science, Amazon Web Services (AWS)