Data Scientist

Data Scientist with NLP, Computer Vision, Machine Learning and Deep Learning expertise. I have experience working with cross-functional teams across the world.

Skills

• Programming Languages: Python, SQL, PySpark
• Artificial Intelligence: Machine Learning, Deep Learning, NLP, Computer Vision, A/B testing, Hypothesis Testing, Statistical Modelling
• Cloud: Azure, GCP, AWS
• Software Development: Git, Docker, Streamlit, Gradio

Experience

Data Scientist, Fractal Analytics

July 2021 - Present

• DT-LLM Research
  • Designed and executed experiments to analyze language generation capabilities of large language models (LLMs) for non-English languages
  • Designed and executed 10+ experiments comparing various LLMs and translation services across 18+ metrics
  • Performed Hypothesis testing to validate the results and recommend best-performing design
  • Presented detailed analysis and recommendations, enabling the client to make architectural decisions for non-English chatbots serving 1.5 million+ users.
• MBL Open AI
  • Assessed the potential of LLMs for automating coding tasks in collaboration with a major international bank.
  • Designed and developed Streamlit applications to demonstrate the capabilities of LLMs in conjunction with Bigquery and Alteryx data and APIs, enhancing automation.
  • Executed POCs using OpenAI’s GPT-4, resulting in a remarkable efficiency improvement of approximately 10-100 times in custom code conversion, with an 83% success rate for complex workflows to Python, SQL. - Additionally, conducted a POC for complex text to BigQuery SQL conversion using GPT-4
• MG Bot
  • Created Django backend APIs and RAG framework for a Chatbot based on a person’s persona
  • Created advanced algorithms to parse 100+ word documents into topics for creating a vector database for the persona and utilized Langchain library to create a chatbot.
• Project Phos
  • Designed and developed the Smart Verification module for a leading reinsurance firm for automatic verification of usage restrictions on data and ensuring compliance using Deep Learning Algorithms and cloud APIs
  • Automated 70% of the verification process, improving efficiency and reducing manual workload
  • Implemented web scraping and data wrangling techniques to curate high-quality training data for the deep learning model.
  • Created, deployed and managed a deep learning model to enable intent classification of legal text documents, improving the module’s functionality and increasing automation by ~100%
  • Created inference pipelines on Azure Databricks to monitor model performance on new data, ensuring consistent accuracy
  • optimized the module code to decrease the execution time of different submodules by up to 5 times
  • Leadership: Mentored interns on NLP and Computer Vision for creating POCs and submodules for the project
  • Nominated for “Client Champion Award” for outstanding work

Education

• B.Tech, IIT (BHU), Varanasi
  • CGPA: 8.96/10

Projects

• Anomaly Detection: Anomaly detection of ECG signals using various ML and DL techniques like CNN Autoencoders
• A/B Testing: Analyzed data from A/B test of a website for revenue optimization and improving the conversion rate for the website.