Education π¨βπ :
I completed my Master's in Computational Data Analytics at Georgia Tech, an institution recognized for its rigorous curriculum and dedication to fostering analytical prowess. I also hold a Bachelorβs Degree in Mechanical Engineering from IIT Kharagpur, one of the most revered engineering institutes in India.
My educational background, underscored by my professional journey, empowers me with a unique confluence of theoretical depth and applied mastery in data science and technology.
Georgia Tech | IIT Kharagpur |
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Awards & Achievements ποΈ :
β Regional Runner-up and 14th across the USA in Purdue Data 4 Good Hackathon - Generative AI for Extractive Question Answering over medical transcripts and patient-doctor dialogues.
β Winner of the Generative AI Case Study Challenge at Prudential Financial amongst all Grad Interns.
β Awarded Leading by Example award in 5 quarters and Champion of the Quarter award in 3 quarters at Innovaccer Inc.
β Bagged an All India Rank of 1336 and 916 in JEE ADVANCED 2015 and JEE MAINS 2015 respectively - Top 0.1%
β Recipient of KVPY (Kishore Vaigyanik Protsahan Yojana) Scholarship - 2015
β Felicitated with Shyamal and Sunanda Ghosh Endownment Scholarship as one of the best incoming sophomore at IIT Kharagpur.
Experience π¨βπ» :
I am a Senior Data Scientist at Prudential Financial within its Chief Data Office.
I am working on projects centered around the applications of Generative AI (LLMs, LMMs), Graph ML & other ML Models catered towards adding business value to the corporate function division, primarily around enterprise and HR operations.
Relevant Tech-Stack:
- AWS (Bedrock, Lex, SageMaker, Comprehend, Kendra)
- LLMs (Azure Open AI GPT-4, Llama-2, Titan, Claude, etc.), RAG based applications (Reranker, RAGAS)
- Streamlit, Docker, LangChain, Llamaindex, OpenSearch
- Python, SQL, Cypher
- Neo4J, Visual Studio Code, BitBucker, JIRA
I possess a multifaceted portfolio of Data Science experience that encompasses a diverse spectrum of domains, ranging from Recommender Systems, Natural Language Processing (NLP), Graph Machine Learning, and experimental design to Statistical modeling (Bayesian vs frequentist) and more. My journey in data science has seen me successfully navigate and excel across these distinct domains, a testament to my adaptability, analytical prowess, and commitment to embracing varied challenges. This well-rounded expertise equips me with the capability to holistically approach complex problems, draw insights from diverse datasets, and construct robust solutions that transcend conventional boundaries.
I did my Internship at Prudential Financial in their Chief Data Office as a Graduate Data Science Intern. I worked on a project centered around exploring the synergies between Graph machine learning and NLP. This experience honed my ability to translate complex technical concepts into actionable insights, ensuring seamless communication between technical and non-technical stakeholders.
In my previous role as a Senior Data Associate at Innovaccer Inc., a leading healthcare analytics company in Silicon Valley, I gained over three years of experience developing data-driven solutions for healthcare systems and provider groups. My work involved creating scalable, deployment-ready projects, such as developing a model to predict patient readmission probabilities and designing a recommendation engine for expanding in-network post-acute care. These projects enhanced my understanding of transforming diverse, unstructured data into accessible, user-centric products, leveraging my skills in Data Science and Analytics.
Here's my Resume, Here you go!
Resume π
Papers (arXiv) π :
- Numerical Reasoning over Financial Reports using LLMs
- Towards a unified Multimodal Reasoning Framework
- EXPLORE: Explainable Song Recommender System
Projects :
- Generative AI for Medical Diagnosis - LLMs for synthetic Tabular Data Generation (Capgemini - Practicum)
- Sales Forecasting for slow-selling SKUβs assisting in inventory management
- SmartChoice: Tailoring User Experiences with Advanced Session-Based AI Recommendations
- RoboChef: Revolutionizing Meal Choices with AI-Powered Image Recognition and Personalized Recommendations
- Spotify Music Popularity Analysis: Regression for unveiling the Dynamics of Song Traction
- SuperMarket Sweep Problem using a variant of Traveling Salesman optimization problem
- Knowledge Distillation using Replication of Stanford Alpaca Paper using QLoRA
Now on to the fun part π
Hobbies β½ π :
I am a big sports buff and I enjoy playing and watching various sports like Soccer, Tennis, Cricket, etc.
I'm a passionate enthusiast for global exploration, endlessly intrigued by the stories, customs, and culinary delights that define each country's unique identity.
I'm an enthusiastic devotee of tech and entrepreneurial podcasts that illuminate the art of value creation in business.