
Data Scientist @Optum || Machine Learning || Gen AI Enthusiastic || Language : C, C++, Python || Interested in doing Projects
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
NIT Jamshedpur
Data Scientist
June 16, 2026 – Present
Cold_email_generator
February 22, 2026 – Present
Cold_email_generator — GitHub repository
View ProjectBankChurnGuard
August 27, 2023 – September 3, 2023
Using data analysis to predict if customers are likely to leave the bank, empowering proactive retention efforts.
View ProjectFeature-Selection-Toolbox
August 3, 2023 – August 9, 2023
Feature-Selection-Toolbox — GitHub repository
View ProjectMultiObjective-Genetic-Algorithm
July 22, 2023 – July 22, 2023
Multiobjective Genetice Algorithm for Feature Selection
View ProjectMultiObjective-Biogeography-Based-Algorithm
July 16, 2023 – July 16, 2023
MultiObjective-Biogeography-Based-Algorithm — GitHub repository
View ProjectNetForensix
July 11, 2023 – January 30, 2024
A smart Network Intrusion detection tool to perform forensics on your network.
View ProjectFake-News-Prediction
July 10, 2023 – September 3, 2023
Fake-News-Prediction — GitHub repository
View ProjectHome-Sweet-Home
October 10, 2022 – October 10, 2022
Console Based Project Home Sweet Home in Python
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a strong interest in data science and machine learning, aligning with a Data Scientist role. The diversity of project topics (network security, finance, news) indicates a broad curiosity. However, all projects are personal, and there is no information on team collaboration or professional work environments, making a comprehensive cultural fit assessment difficult.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and the current role at NIT Jamshedpur has a future start date, suggesting a lack of professional experience. Project descriptions are brief, limiting insight into communication or collaboration styles.