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Malay Bhattacharyya is currently an Associate Professor at Indian Statistical Institute, Kolkata.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Indian Statistical Institute
Data Scientist
June 16, 2026 – Present
DataScienceChallenge-ML4Crypto2024
October 29, 2024 – November 1, 2024
DataScienceChallenge-ML4Crypto2024 — GitHub repository
View ProjectJudgment_Streaming_Logarithmic
October 1, 2023 – October 1, 2023
Judgment_Streaming_Logarithmic — GitHub repository
View ProjectDataScienceChallenge-ML4Crypto2023
September 20, 2023 – October 17, 2023
DataScienceChallenge-ML4Crypto2023 — GitHub repository
View ProjectDataframes
June 15, 2023 – June 30, 2023
This repository will provide few features of data frames
View ProjectDataScienceChallenge-ML4Crypto2022
November 10, 2022 – October 3, 2023
DataScienceChallenge-ML4Crypto2022 — GitHub repository
View ProjectCOVID-19_Panic_Survey
May 26, 2020 – April 23, 2022
A survey of COVID-19 panic on social media users
View ProjectDFSLab
October 30, 2019 – April 23, 2022
Data and File Structures Laboratory - MTech (CS) : First year, First semester : Indian Statistical Institute, Kolkata
View ProjectCultural Fit Analysis
The candidate's project history shows a strong focus on personal data science challenges and academic projects, which aligns with a research-oriented or technically deep culture. However, the lack of team-based projects or detailed descriptions of collaboration makes it difficult to fully assess cultural fit for a collaborative industry role. The experience level of 0 and a single current role starting in the future (2026) suggest this candidate is likely a recent graduate or still pursuing education, which might require mentorship and integration into a professional team environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's experience level is listed as 0, and there is only one current role with no details on responsibilities or achievements. Project descriptions are minimal, limiting insight into collaboration or problem-solving approaches.