About

Hello! My name is Abhijit Gupta, and I am a senior at Yale University majoring in Computer Science. I have previously interned with Jane Street, Sentry.io, Gatherly, and RTI International. In my free time, I work on side projects including GitHub Trends, Statbotics, and Hopscotch. Please feel free to reach out!
Abhijit Gupta

Experiences

  • Quant Trading @ Jane Street (NYC, Summer 2022): Attended classes, participated in mock-trading, and worked on data analysis projects with trading desks. Further details omitted due to IP restrictions.
  • Software Engineering @ Sentry.io (Remote, Fall 2021): Worked with the Data Team based in San Francisco building ETL pipelines for 100M+ daily messages from the Sentry.io platform. Used Apache Kafka, PySpark, GCS, AirFlow, BigQuery, and DataDog to prototype a batch processing pipeline with increased throughput and scalability.
  • Quant Trading @ Jane Street (NYC, Summer 2021): Attended classes, participated in mock-trading, and worked on two data analysis projects with trading desks. Further details omitted due to IP restrictions.
  • ML Researcher @ Yale IMG Lab (Yale, 2020-21): Built a deep learning pipeline analyzing social group phenomena for human-robot interaction using graph neural networks, improving metrics over state-of-the-art heuristic baselines. Paper available here.
  • Software Engineering @ Gatherly (Remote, Fall 2020): Spearheaded data analytics initiative analyzing 1M+ user actions to extract actionable insights for online event hosts. Implemented an automated payment system using the Stripe API with subscriptions, discounts, and tiered pricing. Used AWS, NodeJS, ReactJS, and Stripe.
  • Data Analyst @ RTI International (Remote, Summer 2020): Designed campus monitoring dashboard to visualize temporal building ocupancy. Implemented automated demand prioritization system for BI team, reducing manual labor by 80%. Used Microsoft SQL Server, Power BI, and Excel.
  • ML Researcher @ Yale LILY Lab (Yale, Fall 2019): Trained machine learning model to classify salient events in 2D physics simulations with 91% accuracy. Contributed to research paper studying implicit physical reasoning in NLP. Paper available here.

Projects

Recently, I have worked on GitHub Trends, Statbotics.io, and Hopscotch. More details coming soon!