yellowshark AG
Expleo Technology Switzerland
Data Scientist – Time Series & Anomaly Detection
Temps plein
📋
Description du poste
Expleo Technology Switzerland est a la recherche d'un(e) Data Scientist – Time Series & Anomaly Detection pour son site de CH.
Expleo offers a unique offer of integrated engineering, quality and strategic consulting services for digital transformation. In a context of technological acceleration, we are the trusted partner of companies that innovate. We help them develop a competitive advantage and improve the lives of millions of people.
Joining Expleogroup means 17,000 employees in 30 countries, but also:
• Have technical and human support for each project and effective follow-up of your career
• Carry out training to develop professional skills
• Participate in dedicated special events
• Integrate a dynamic team
To join our Team of Data consultants based in
Geneva area
, we are looking for a
Data Scientist – Time Series & Anomaly Detection (m/w)
As AI specialist , you will contribute to the development of an advanced machine learning solution in the motorsport and automotive domain.
The project focuses on building a robust anomaly detection system, combining data engineering, machine learning and software engineering practices to transform complex data into actionable technical insights.
Your mission:
• Develop and optimise machine learning models for time-series analysis and anomaly detection
• Design and implement data pipelines from raw data to ML-ready datasets
• Build explainable AI solutions enabling users to understand model outputs
• Define performance indicators and analytical frameworks
• Establish MLOps foundations including experiment tracking, model lifecycle management and reproducible workflows
• Produce technical documentation and support knowledge transfer. You will collaborate with experienced engineering and data teams in a highly technical environment combining AI, software development and advanced analytics.
Your Profile:
•
You have 6 years minimum parcours professionnel in Machine Learning Engineering/
Data Science ideally
in motorsport, automotive, aerospace environments.
•
Strong expertise in time-series data and anomaly detection
• Advanced Python skills and experience with ML frameworks
• Experience developing end-to-end machine learning solutions
• Knowledge of MLOps practices and software engineering standards
• Ability to translate complex technical outputs into clear insights
• Fluent French and English mandatory
AVENUE DE RHODANIE 60
1013 Geneve
Rejoignez Expleo Technology Switzerland et donnez un nouvel elan a votre carriere.
Expleo offers a unique offer of integrated engineering, quality and strategic consulting services for digital transformation. In a context of technological acceleration, we are the trusted partner of companies that innovate. We help them develop a competitive advantage and improve the lives of millions of people.
Joining Expleogroup means 17,000 employees in 30 countries, but also:
• Have technical and human support for each project and effective follow-up of your career
• Carry out training to develop professional skills
• Participate in dedicated special events
• Integrate a dynamic team
To join our Team of Data consultants based in
Geneva area
, we are looking for a
Data Scientist – Time Series & Anomaly Detection (m/w)
As AI specialist , you will contribute to the development of an advanced machine learning solution in the motorsport and automotive domain.
The project focuses on building a robust anomaly detection system, combining data engineering, machine learning and software engineering practices to transform complex data into actionable technical insights.
Your mission:
• Develop and optimise machine learning models for time-series analysis and anomaly detection
• Design and implement data pipelines from raw data to ML-ready datasets
• Build explainable AI solutions enabling users to understand model outputs
• Define performance indicators and analytical frameworks
• Establish MLOps foundations including experiment tracking, model lifecycle management and reproducible workflows
• Produce technical documentation and support knowledge transfer. You will collaborate with experienced engineering and data teams in a highly technical environment combining AI, software development and advanced analytics.
Your Profile:
•
You have 6 years minimum parcours professionnel in Machine Learning Engineering/
Data Science ideally
in motorsport, automotive, aerospace environments.
•
Strong expertise in time-series data and anomaly detection
• Advanced Python skills and experience with ML frameworks
• Experience developing end-to-end machine learning solutions
• Knowledge of MLOps practices and software engineering standards
• Ability to translate complex technical outputs into clear insights
• Fluent French and English mandatory
AVENUE DE RHODANIE 60
1013 Geneve
Rejoignez Expleo Technology Switzerland et donnez un nouvel elan a votre carriere.
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📄 Quels documents fournir ? ▾
CV antichronologique (2 p. max, photo recommandée), lettre de motivation personnalisée, diplômes, certificats de travail et références professionnelles.
✍️ Comment rédiger sa candidature ? ▾
Votre CV doit reprendre les mots-clés de l'offre et quantifier vos résultats. La lettre (1 page) doit être adressée nominativement et mentionner votre disponibilité et vos prétentions salariales.
⏱️ Quels délais de réponse ? ▾
Accusé de réception sous 2–5 jours. Première réponse sous 1–3 semaines. Entretien et décision finale sous 4–8 semaines. Relancez poliment après 2 semaines sans nouvelles.
💰 Salaires et négociation ▾
Les salaires sont exprimés en brut annuel. Le 13e mois est très courant. Négociation possible au moment de l'offre. Consultez jobs.ch pour des benchmarks par secteur.
🌍 Travailler en Suisse en tant qu'étranger ▾
Ressortissants UE/AELE : permis L (< 1 an) ou B (≥ 1 an), démarches simplifiées. Hors UE/AELE : permis B demandé par l'employeur, soumis à des quotas annuels.
💼 Préparer l'entretien ▾
Renseignez-vous sur l'entreprise et ses produits. Préparez des exemples concrets de réalisations. Arrivez 10 min en avance. Posez des questions sur les prochaines étapes du processus.