I am a Data Scientist with a Ph.D. in Physics, specializing in machine learning, data analysis, and scientific computing. My experience spans building robust models for complex, noisy datasets and applying model distillation techniques to compress and accelerate deep learning workflows. I have strong skills in Python, SQL, and modern machine learning frameworks, and am experienced in developing end-to-end machine learning systems with automated workflows, monitoring, and model management to ensure reliable deployment in production environments. Currently based in Geneva, Switzerland, I am open to remote opportunities. My work includes leading international research teams, applying decision tree-based models for rare event detection, and tailoring machine learning algorithms for low-latency applications including real-time environments and FPGA-based systems. I am passionate about creating data-driven solutions and mentoring students in applied machine learning and data analysis.…

Rajat Gupta

I am a Data Scientist with a Ph.D. in Physics, specializing in machine learning, data analysis, and scientific computing. My experience spans building robust models for complex, noisy datasets and applying model distillation techniques to compress and accelerate deep learning workflows. I have strong skills in Python, SQL, and modern machine learning frameworks, and am experienced in developing end-to-end machine learning systems with automated workflows, monitoring, and model management to ensure reliable deployment in production environments. Currently based in Geneva, Switzerland, I am open to remote opportunities. My work includes leading international research teams, applying decision tree-based models for rare event detection, and tailoring machine learning algorithms for low-latency applications including real-time environments and FPGA-based systems. I am passionate about creating data-driven solutions and mentoring students in applied machine learning and data analysis.…

Available to hire

I am a Data Scientist with a Ph.D. in Physics, specializing in machine learning, data analysis, and scientific computing. My experience spans building robust models for complex, noisy datasets and applying model distillation techniques to compress and accelerate deep learning workflows. I have strong skills in Python, SQL, and modern machine learning frameworks, and am experienced in developing end-to-end machine learning systems with automated workflows, monitoring, and model management to ensure reliable deployment in production environments.

Currently based in Geneva, Switzerland, I am open to remote opportunities. My work includes leading international research teams, applying decision tree-based models for rare event detection, and tailoring machine learning algorithms for low-latency applications including real-time environments and FPGA-based systems. I am passionate about creating data-driven solutions and mentoring students in applied machine learning and data analysis.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert

Language

English
Fluent
French
Beginner

Work Experience

Data Analyst at CMS@LHC (CERN and Panjab University)
January 1, 2022 - August 30, 2025
Analyzed experimental datasets with millions of records to extract structured patterns and validate data-driven hypotheses. Coordinated multi-year projects involving data quality checks, statistical evaluation, and reporting of key metrics. Led communication and documentation for collaborative research projects.
Data Scientist at ATLAS@LHC (CERN and University of Pittsburgh)
January 1, 2022 - Present
Lead an international team of 10 researchers on a machine learning-based rare event detection project analyzing over 1 billion samples, targeting signals occurring in less than 0.1% of cases. Applied decision tree–based ML models to suppress dominant background noise, achieving a 13% improvement in sensitivity for rare signal detection. Developed model distillation workflows to convert deep learning outputs into lightweight decision tree models, enabling significantly faster and more resource-efficient inference. Collaborated with hardware engineers to tailor ML algorithms for low-latency applications (sub-3 microseconds), including real-time environments and FPGA-based systems. Built data-driven compression solutions for edge memory platforms, integrating ML techniques for efficient storage and retrieval. Mentored one PhD and two undergraduate students in applied machine learning, data analysis, and communication. Coordinated multi-year projects involving data quality checks, statis

Education

Ph.D. in Particle Physics at University of Pittsburgh & CERN
January 1, 2022 - August 30, 2025
M.Sc. Physics at Panjab University
January 11, 2030 - August 30, 2025

Qualifications

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Industry Experience

Life Sciences, Software & Internet, Professional Services, Education, Other