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Data Engineer or Data Scientist

CERN

Genf · On-site Lead 5d ago

About the role

About

Do you want to apply your Data Science and AI expertise to one of the world's most complex scientific and engineering environments?
Join CERN and take a leading role in developing an AI driven prescriptive maintenance and operational assistance platform for the Large Hadron Collider (LHC). You will develop a proof of concept using LHC Run 3 data, then lead testing and validation on representative systems within the TE Department, with the goal of achieving full deployment for Run 4. Collect and formalise operational use cases and user stories with engineers and maintenance experts; Define system requirements and draft solution architecture for an AI-driven prescriptive maintenance platform.

Responsibilities

  • Perform data pre‑processing, feature engineering, and exploratory analysis to prepare datasets for modelling.
  • Design and execute machine learning experiments for anomaly detection, failure prediction, and prescriptive recommendations.
  • Package and deploy models into production environments through APIs and containerised services (e.g. Contribute to system integration, testing, performance monitoring, and iterative improvement of deployed models.

Requirements

  • Academic background in Data Science, Computer Science, Engineering, Applied Mathematics, or a related quantitative field.
  • Experience working on applied machine learning or data‑driven projects addressing real‑world operational or engineering problems.
  • Experience with version control systems (e.g. Proficiency in Python for data analysis and machine learning (e.g. Understanding of machine learning techniques relevant to time series analysis, anomaly detection, and predictive modelling.
  • Knowledge of data pre‑processing, feature engineering, and exploratory data analysis (EDA).
  • Spoken and written English, with a commitment to learn French.
  • You have a professional background in Data Science, Computer Science, Mathematics (or a related field) and have either:
    • a Master's degree with 2 to 6 years of post‑graduation professional experience;
    • or a PhD with no more than 3 years of post‑graduation professional experience.
  • ~ You have never had a CERN fellow or graduate contract before.

Benefits

  • Data Science & Data Analytics
  • Coverage by CERN’s comprehensive health insurance scheme (for yourself, your spouse and children), and membership of the CERN Pension Fund.
  • Family, child and infant monthly allowances depending on your individual circumstances.
  • On‑the‑job and formal training including language classes.

Diversity & Inclusion

Our groundbreaking work brings together not only physicists but also a diverse range of professionals from engineering, technical, scientific, and administrative fields. Diversity is a core value of CERN since its foundation, and it remains central to our mission and continued success.

Requirements

  • Experience working on applied machine learning or data-driven projects addressing real-world operational or engineering problems
  • Experience with version control systems
  • Proficiency in Python for data analysis and machine learning
  • Understanding of machine learning techniques relevant to time series analysis, anomaly detection, and predictive modelling
  • Knowledge of data pre-processing, feature engineering, and exploratory data analysis (EDA)
  • Spoken and written English, with a commitment to learn French
  • You have a professional background in Data Science, Computer Science, Mathematics (or a related field) and have either: a Master's degree with 2 to 6 years of post-graduation professional experience; or a PhD with no more than 3 years of post-graduation professional experience
  • You have never had a CERN fellow or graduate contract before

Responsibilities

  • Collect and formalise operational use cases and user stories with engineers and maintenance experts
  • Define system requirements and draft solution architecture for an AI-driven prescriptive maintenance platform
  • Perform data pre-processing, feature engineering, and exploratory analysis to prepare datasets for modelling
  • Design and execute machine learning experiments for anomaly detection, failure prediction, and prescriptive recommendations
  • Package and deploy models into production environments through APIs and containerised services
  • Contribute to system integration, testing, performance monitoring, and iterative improvement of deployed models

Benefits

health insuranceCERN Pension FundFamily, child and infant monthly allowancesOn-the-job and formal traininglanguage classes

Skills

APIPython

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