RITESH KUMAR

Data Scientist

https://talent.gravityer.com/ritesh-kumar-10

Assistant Professor, TCG CREST RISE, Kolkata, India | Past: Eric & Wendy Schmidt AI in Science Fellow @ UChicago

TCG CREST

Key Strengths

Extensive experience with Python and Jupyter Notebook for scientific computing and data analysis.
Demonstrated ability to apply machine learning (ML) in scientific research, particularly in materials science and chemistry.
Experience with active learning and Bayesian ML, indicating a strong foundation in advanced ML techniques.
Projects show a strong focus on data extraction, simulation processing, and high-throughput experimentation, aligning well with data scientist responsibilities.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily academic/research-oriented, focusing on scientific data and simulations. While this demonstrates strong analytical capabilities, the diversity of application domains outside of scientific research is limited. The current role as 'Data Scientist' at TCG CREST aligns with the target role, but the lack of detailed experience descriptions makes it difficult to fully assess cultural fit beyond a research-heavy environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

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Projects

vigyandeep-tutorial-2026

June 3, 2026 – Present

Tutorial on Bayesian ML as part of Vigyandeep lecture series on AI

View Project

ai4en

October 26, 2025 – Present

My personal website

View Project

AtomBridge

September 5, 2025 – November 11, 2025

Interface between TEM images and DFT

View Project

curaitor-agent

August 20, 2025 – Present

AI agent for scientific data extraction

View Project

AL-anode-free

February 12, 2025 – December 12, 2025

Codes and data for active learning for next-generation battery electrolyte optimization

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curaitor

June 20, 2024 – February 23, 2025

curaitor — GitHub repository

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ai-sci-hackathon-2024

April 30, 2024 – May 8, 2024

Resources for the 2024 Schmidt Fellows AI+Science hackathon

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Polymer-Molecular-Dynamics

June 16, 2022 – June 15, 2022

Perform high-throughput polymer MD simulations for various polymer properties with ease

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HT-iML_Photocatalysis

September 21, 2021 – December 14, 2021

Datasets and codes for the paper: "Chemical Hardness-Driven Interpretable Machine Learning Approach for Rapid Search of Photocatalysts"

View Project

Simulation_processing

January 10, 2017 – Present

Simulation_processing — GitHub repository

View Project

Key Strengths

Extensive experience with Python and Jupyter Notebook for scientific computing and data analysis.
Demonstrated ability to apply machine learning (ML) in scientific research, particularly in materials science and chemistry.
Experience with active learning and Bayesian ML, indicating a strong foundation in advanced ML techniques.
Projects show a strong focus on data extraction, simulation processing, and high-throughput experimentation, aligning well with data scientist responsibilities.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights.

RITESH KUMAR

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit