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M.Tech. CS ISI Kolkata 2020-22 (Data Science) | B.Tech EE NIT Kurukshetra 2014-18
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Indian Statistical Institute, Kolkata
Data Scientist
June 14, 2026 – Present
Sentiement-Analysis-on-Mother-s-Day-Tweets
April 24, 2024 – April 24, 2024
Sentiement-Analysis-on-Mother-s-Day-Tweets — GitHub repository
View ProjectLLM-CodeEnhancer
March 20, 2024 – March 20, 2024
Using CodeLlama to make given python to follow PEP standards
View ProjectQuantitative-Analyst-Intern-Assignment
June 16, 2021 – June 16, 2021
This repository contains the files pertaining to my assignment done as part of FalconX interview process
View ProjectNeural-Networks-From-Scratch
June 14, 2021 – June 14, 2021
I will be uploading the notebooks of neural networks done from scratch as part of Neural Networks coursework. I will also upload algorithms done from scratch on my own interest apart from coursework
View ProjectTime-Series-Analysis
June 13, 2021 – June 15, 2021
The Datasets & Notebooks in which I practiced while learning Time Series Analysis
View ProjectYoutube_Data_Scraping
June 13, 2021 – June 13, 2021
Youtube Data Scraping project (as part Kofluence Internship process)
View ProjectInformation-Retrieval-Assignments
June 9, 2021 – June 9, 2021
Information-Retrieval-Assignments — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects show a strong inclination towards self-learning and exploration in data science. The diversity of project topics (LLMs, sentiment analysis, time series, data scraping) indicates a broad interest within the field. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration or cultural alignment in a work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and the only listed 'experience' is a future role starting in 2026, which suggests a lack of professional work experience.