Jun 2023 – Feb 2024 · 8 mos · Bengaluru, Karnataka, India · On-site

Sep 2020 – Dec 2022 · 2 yrs 3 mos · Chennai, Tamil Nadu, India

• Worked on extending OpenMP with Low-Level Synchronisation Primitives.
• Extended OpenMP to allow point to point synchronisation between different iterations of a parallel for loop.

Jun 2019 – Jan 2020 · 7 mos

• Developing Predictive Models using Time Series and Heuristic Approaches to forecast the cash received on a future span of 180 days.

Apr 2019 – Jun 2019 · 2 mos

• Was actively a part of the team Rivana DataSciences wherein I provided active solutions to the problems of
• 1) Payment Date Prediction wherein we deploy machine learning models which utilize the historical data to detect patterns and predict the expected payment date of the invoice. Clients handled include Walmart, Danone, HID, FitBit,etc.
• 2) Promise to Pay wherein we use classification models to predict whether a promise to pay an invoice is kept or broken. Client handled include Shurtech.
• 3) Developed a Machine Learning Pipeline which automates the entire Payment Date Prediction solution process to generate machine learning models in an automated manner with minimal human intervention.

Jul 2018 – Apr 2019 · 9 mos

• Was actively a part of the team Rivana DataSciences wherein I provided active solutions to the problems of
• 1) Payment Date Prediction wherein we deploy machine learning models which utilize the historical data to detect patterns and predict the expected payment date of the invoice.
• 2) Promise to Pay wherein we use classification models to predict whether a promise to pay an invoice is kept or broken.
• 3) Developed a Machine Learning Pipeline which automates the entire Payment Date Prediction solution process.

May 2018 – Jun 2018 · 1 mo · Kolkata Area, India

• Me and my team were actively involved in building a web development project for developing a module for a banking application. The module developed included the processes involved to originate a loan for a customer. Was involved in studying the existing solution and the architecture and suggest new methods for further use cases and also fixing any errors arising in the already built solution, per se.