
Chasing the cheese!
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JP Morgan Chase & Co.
Data Scientist
June 12, 2026 – Present
Community-Living-DBMS
November 23, 2022 – December 27, 2022
DBMS for an application that ensures the safety and convenience of gated societies. It offers features to create a wholesome community living experience and improve security standards around gated communities.
View ProjectDerby-Horse-Racing
September 11, 2022 – December 20, 2022
Big Data Derby Racing Dataset's Analysis Project
View ProjectSemantic-Segmentation-on-Martian-Terrain
August 14, 2022 – January 8, 2023
In this research, a novel approach has been presented for multi-label semantic segmentation of the martian terrain for navigation using variants of a transformer model - SegFormer, which has resulted in a commendable accuracy of 90.86% and mIoU of 83.55% on the AI4Mars dataset
View Projectcfg-bangalore-food-bank
June 27, 2022 – June 27, 2022
MERN Stack Donation portal for Bangalore Food Bank http://bangalorefoodbank.com
View ProjectOS-Lab-UE20CS254-Example-Codes
February 4, 2022 – May 3, 2022
Operating Systems (UE20CS254) example codes shared in labs. Jan-May 2022.
View ProjectEmployeeManagement-MERN
November 19, 2021 – June 17, 2023
Web application that facilitates authentication, leave requests, CRUD operations for employees for a particular small/medium organization, handled by an authoritative HR role in the same organization.
View ProjectSales-Report-Generator
August 7, 2021 – October 10, 2021
This is a project about building a sales data report generator web application using Django and JavaScript, to visualize the sales data, and upload sales records from csv files & generate pdfs.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and academic, showing a breadth of technical interests but limited exposure to collaborative, large-scale industry projects. The current role at JP Morgan Chase & Co. as a Data Scientist aligns with the target role, but without further details on responsibilities or team dynamics, cultural fit is difficult to ascertain. The project diversity is good, but the depth of engagement in a team setting is not evident.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric or English test scores are available, and project descriptions do not provide insight into collaboration or problem-solving approaches.