Help & Supportcareers@gravityer.com
Software Developer at D. E. Shaw | Prep Fellow Fall'21 @MLH-Fellowship
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
D. E. Shaw
Data Scientist
June 20, 2026 – Present
academicpages.github.io
October 28, 2024 – October 28, 2024
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
View Projectavengers
September 29, 2023 – September 29, 2023
This repo contains the avengers details.
View Projectscigenom-auth
September 6, 2022 – September 10, 2022
This repo contains the auth microservice for authentication.
View Projectjob_application_review
August 26, 2022 – August 27, 2022
A job application review application
View Projectcentral-library
May 11, 2022 – May 11, 2022
A web app for central library where users can add books, update book details and delete books.
View Projectfood-classification
March 24, 2022 – March 24, 2022
A Django app that alerts parents when their kids are provided with non-food items
View Projectdoclib
April 5, 2021 – February 22, 2022
A document library that integrates with multiple data sources (like digiLocker, Google Drive, local storage etc.) and storage services (like S3 and Google Cloud Storage) and uploads data from these data sources to the chosen storage service.
View ProjectCultural Fit Analysis
The candidate's projects are all personal and primarily focus on web development and basic Python applications, with limited explicit data science projects. While there is a stated role as 'Data Scientist' at D. E. Shaw, the project history does not strongly align with typical senior data scientist responsibilities such as advanced statistical modeling, machine learning engineering, or big data processing. The diversity of projects is present, but the depth in data science is not evident from the descriptions. This suggests a potential gap in cultural fit for a senior data scientist role requiring extensive prior experience in core data science domains.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's projects are primarily personal and lack details on team collaboration or problem-solving methodologies.