Master of Science in Data Science

2023 - 2025

Harvard University, Cambridge, MA

Courses: NLP, Data Science, Systems Development for Computer Science, Artificial Intelligence

Bachelor of Technology

2019 - 2023

Indian Institute of Technology (IIT) Bombay, India

Major: Metallurgical Engineering and Materials Science

Minor: Data Science and Artificial Intelligence

Courses: Materials Technology, Advanced Machine Learning, Optimization Models, Programming for Data Science, Linear Algebra, Numerical Analysis, Probability and Stochastic Processes

Operation and Logistics Manager | Abhyuday, IIT Bombay

May 2021 - April 2022

• Lead a 2 tier team of 100+ volunteers to organize 50+ events & campaigns, 5+ nationwide competitions
• Negotiated the Sponsored deals in Abhyuday for CR Program Merchandise worth INR 0.5 Million
• Executed month-long campaign ‘SANGHARSH’ in collaboration with UNICEF India reaching 2 M+ people
• Targeted 10k+ underprivileged students of 100+ schools under Career Counseling with 50% Y-O-Y growth

Marketing Coordinator | The Entrepreneurship Cell, IITB

May 2020 - April 2021

• Worked with a 20-membered team to ideate the deliverables to fit in the online ecosystem
• Explored strategic association with high-ranking corporates and closed sponsorship deals to facilitate the execution of events
• Ideated and executed multiple publicity campaigns to increase the reach of Eureka - Asia’s largest B-model competition with 12.5K entries and prizes worth INR 5 million

Team Member | The Developer’s Community, IIT Bombay

May 2020 - March 2021

• Envisioned as the group of best developers of the Institute, the team is responsible for developing and maintaining InstiApp, and other dev/tech related projects in the Institute
• Worked in a team of 10 to develop a resume points verification portal using angular, node.js, SQL database

Junior Data Scientist in AI for Healthcare

June’23-July’23

Innoplexus, Pune India

• Utilized Bayesian Inference to identify key emerging topics from medical publications for pre-clinical trial research
• Worked on topic modeling, sentiment analysis, information retrieval, word embedding, and n-gram language models
• Gave a company-wide Linkedin live conference on Causality and it’s applications in Machine Learning

Data Science Intern

Publicis Sapient, Bangalore India

May’22-July’22

Received pre-placement offer from the company

• Devised a comprehensive end-to-end system to generate Credit Scores for MSMEs in compliance with the US Laws using alternative data sources to provide easier access to loans from financial institutions
• Integrated Explainable AI systems using SHAP to maintain transparency between our systems and the end user
• Formulated a pipeline using Kubeflow and Elyra, used docker and Kserve to deploy the best model and dockerized our front-end application built using Streamlit for deployment using Amazon AWS ECR
• Encrypted the financial dataset and stored it in MySQL database to maintain the anonymity of our end user

Data Science and Analytics Intern

Freespace by Workplace Fabric, United Kingdom

Jan’22-May’22

Received a Letter of Recommendation from Business Intelligence Head - Founders Office

• Interacted with clients to understand the business problem and built Tableau dashboards to obtain inferences
• Employed time series forecasting machine learning and AI algorithms to identify the sensors that are expected to be dysfunctional by analyzing various factors causing the fault (e.g., Battery drainage trends)
• Predicted future workplace occupancy percentages of companies in the UK and provided solutions for efficient modern workplaces to clients like MarshMcLennan and Mastercard

Machine Learning Engineering Intern

ClearExam

Jun’21-Aug’21

User-Customized Recommendation chatbot

• Responsible for preparing SoW, business process, data model and associated business requirement documentation
• Studied research papers related to knowledge tracking systems and implemented two using keras and tensorflow
• Developed and compared Logistic Regression, Random Forest Classifier, KNN, SVM, LSTM models
• Utilized ensemble learning algorithms like bagging and boosting to combine several models and also built the recommendation system using reinforcement learning (Deep Q-learning)