Apr 2022 – Aug 2024 · 2 yrs 4 mos · Bengaluru, Karnataka, India

Jul 2021 – Mar 2022 · 8 mos · Bengaluru, Karnataka, India

Jul 2020 – Jun 2021 · 11 mos · Bengaluru, Karnataka, India

• Quantitative role in the Private Wealth Management (PWM) Strats team that develops
• financial applications and investment strategies for various client advisory teams.
• Worked on Calculating and adding metrics to a Financial Risk Management tool
• based on React which involved populating the memSQL Database and setting up
• resolvers on the GraphQL server.
• Optimised the memSQL Database to increase performance by taking into
• consideration the Distributed computing model of the database.
• Built infrastructure to set up a new option writing strategy for the business team and
• also the risk assessment framework for the strategy
• Developed applications for creation of grantor trusts, calculation of projected tax
• savings with visualizations on dashboards and frameworks to automate report
• generation and approval workflow.
• Parallellized computation of risk metrics for a UI dashboard using a internal tool that
• calls C++ threads, as a result the render time reduced from 30 seconds to 2 seconds.
• Worked on setting up the QA pipeline for proper integration and for further risk
• calculations of United Capital Accounts ( A firm Acquired By GS ), This included
• fetching Data from multiple APIs and Data Warehouses.

May 2019 – Jul 2019 · 2 mos · Bengaluru, Karnataka, India

• Built a simulation to bring about the results of Federated learning with differential
• privacy in next word prediction by adding Gaussian noise to the client data.
• Developed a hierarchical text classifier model using agglomerative clustering for
• grouping and improving the prediction of trends on Samsung keyboard.

Dec 2018 – Jan 2019 · 1 mo · Bangalore

• Involved in designing a ML based model to solve an internal problem, addressing
• routing congestion in a chip designing tool using neural-networks.
• Worked on optimisation and statistical analysis of the model, which is used to make
• decisions for selecting a certain algorithm for the computation of a NP-hard problem.