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Data Scientist

Entreprise
Localisation
Paris, Île-de-France
Sur site
Type de contrat
CDI
Niveau
Senior

Salaire du marché

Médiane du marché
52k€
Estimation
45k€fourchette habituelle55k€

Cette offre n'affiche pas de salaire. D'après 10 offres pour ce poste (Senior, France), le marché se situe autour de 52k€ (45k€–55k€).

Salaire du marché pour Data Scientist (Senior) en France : médiane 51 500 €/an, P25–P75 : 45 000–55 000 €/an, n = 10 offres. Salaire Python à Paris

Baromètre TJM et salaires IT

Description du poste

Job Description
Location: Paris, France
Job reference #: 34076
Contract type: Permanent
Language requirements: Fluent in French and English
At Eni, we are looking for a Data Scientist to join Eni Plenitude France.
About Plenitude
Plenitude is an energy company that integrates the retail business and renewable generation with self-consumption and electric mobility solutions, providing energy and gas to more than 10 million homes and businesses across Europe, which offers a range of great professional opportunities for the whole team. This partnership represents a major European project integrating the renewable energy business with the retail business, which will enable us to progressively increase our offering of services, infrastructure, and green energy for our customers, providing our team with greater visibility and professional growth.
Main responsibilities:

  • Design, develop and deploy Machine Learning, Deep Learning and Generative AI solutions to address business challenges.
  • Build, validate and optimise predictive, prescriptive and optimisation models.
  • Perform advanced data exploration, feature engineering and dataset preparation.
  • Lead model training, validation, hyperparameter tuning and performance optimisation.
  • Develop AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and prompt engineering techniques.
  • Design and implement AI agents and agentic workflows to automate processes and support decision-making.
  • Develop and maintain AI and Machine Learning pipelines, integrating APIs, enterprise data sources and business systems.
  • Apply explainability and interpretability techniques to ensure transparency and trust in AI solutions.
  • Promote Data Science, AI Engineering, MLOps and LLMOps best practices, including testing, version control and responsible AI principles.
  • Define monitoring frameworks covering model performance, drift detection, retraining and cost optimisation.
  • Design and execute experimentation frameworks, including A/B testing and causal analysis.
  • Generate insights and advanced analytics to support business decision-making.
  • Collaborate with Data Engineering and business teams to industrialise and operationalise AI solutions.
  • Contribute to AI innovation initiatives and evaluate emerging technologies and use cases.
  • Act as a technical reference for Data Science, Machine Learning and AI Engineering.
Skills and experience required:
  • Master's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related quantitative discipline.
  • Significant experience in Data Science, Machine Learning, AI Engineering or a related field.
  • Strong expertise in Machine Learning, Deep Learning, Statistical Modelling and Generative AI.
  • Experience with predictive modelling, optimisation techniques and advanced AI methodologies.
  • Proficiency in Python and Machine Learning/AI development libraries.
  • Experience across the full Machine Learning lifecycle, from development and deployment to monitoring and optimisation.
  • Hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and prompt engineering.
  • Knowledge of Agentic AI frameworks and AI agent development.
  • Experience integrating AI solutions with APIs, enterprise data sources and business applications.
  • Familiarity with MLOps and LLMOps practices.
  • Experience with cloud-based AI platforms; Azure and Databricks experience preferred.
  • Knowledge of software engineering best practices, including version control, testing and CI/CD.
  • Strong analytical, problem-solving and communication skills.
  • Ability to work effectively with cross-functional teams and stakeholders.
How to apply:
  • Applications are only accepted through our online application system.
  • Please upload your CV in English.
About Eni
Eni is a global energy company operating in 61 Countries, with over 30,000 employees. Originally an oil & gas company, it has evolved into an integrated energy company, playing a key role in ensuring energy security and leading the energy transition. Eni's goal is to achieve carbon neutrality by 2050 through the decarbonization of its processes and of the products it sells to its customers. In line with this goal, Eni invests in the research and development of technologies that can accelerate the transition to increasingly sustainable energy. Renewable energy sources, bio-refining, carbon capture and storage are only some examples of Eni's areas of activity and research. In addition, the company is exploring game-changing technologies such as fusion energy - a technology based on the physical processes that power stars and that could generate safe, virtually limitless energy with zero emissions.
Working at Eni
At Eni we believe in enterprising people, capable of making a difference and making their contribution with passion and innovation, to respond to the global challenges of the energy transition. For us, the skills and attitudes of each individual, continuous training, and diversity and inclusion are fundamental. We promote flexible ways of working with particular attention to well-being, welfare and work life-balance. Eni will evaluate applications considering plurality and diversity as sources of enrichment. If your application is assessed to be among those most in line with the required profile, you will be contacted to continue the selection process. Whatever your ambition, at Eni you can find the tools to make it happen.
Energy for action takers

Exigences du poste

Compétences requises

  • Scaled Agile
  • A/B Testing
  • Data Science
  • LLM
  • Artificial Intelligence
  • Monitoring / Observability
  • MLOps
  • Data Engineering
  • Microsoft Teams
  • Python
  • Machine Learning
  • Deep Learning
  • Azure
  • CI/CD
  • Databricks
  • Agentic AI / Agents IA
  • Prompt Engineering
  • RAG

Un plus

  • Anglais
  • API Development
  • LLMOps
  • QA Testing
  • Cloud
  • Makefile
  • GenAI

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