Industry Experience

Working in the Timelines Quality team. The teamโ€™s mission is to show users the content they care about by building relevance and machine learning models and systems. Every time users see new tweets, nearly half a billion daily tweets are evaluated to organize and deliver the best timeline experience.

Technologies: Python | Scala | Scalding | Hadoop | Airflow | BigQuery | GCP | Tensorflow

Worked for Amazon Expansions and Exports - Tech team which enables customers to buy eligible products internationally. I was involved in projects around:

Technologies: AWS services | Java | Python | Jupyter Notebook

Side hustles at work:

I interned in the DataForge team which provides a platform for running Big Data operational workloads consistently within service level agreement, obviating the need to learn, set up, and manage Big Data technologies in order to support operational business use cases. I worked towards designing and implementing:

This was particularly challenging as it entailed handling highly concurrent and complex scenarios arising due to the distributed nature of Hive and the fact that Hive is not designed to handle transactional data and operations.

Technologies: Java | Hive | DynamoDB

Arcesium spun out of the D. E. Shaw Group. I worked there in the Arcesium/Tech division as a primary developer for the STP (Straight Through Processing) team. Some of my important responsibilities include:

Technologies: Java | Spring | MyBatis | SQL Server | Git

Research Experience

Under Prof. Julian McAuley's guidance, I worked on several user behavior modeling and NLP problems and published following articles:

I worked under the guidance of Prof. Balaraman Ravindran and contributed to two research problems, focusing on the development of scalable Bayesian algorithms for Recommender Systems.

I was a part of Summer Fellowship Programme of IIT Madras and worked here under the guidance of Prof. Balaraman Ravindran in the field of Statistical Machine Learning. I did a project on Collaborative Tweet Recommendation where I used Collaborative Filtering to efficiently recommend relevant tweets to users.