Data Scientist/AI Engineer

Plenitude; Levallois-Perret; On-site; EUR 70,000 - 120,000; Full time

Job summary

Plenitude is seeking a Data Scientist to design, develop and deploy advanced AI/ML solutions in Paris. You will build predictive and prescriptive models, perform feature engineering, and lead model training and evaluation.

You’ll work with Data Engineering and business teams to scale AI initiatives and ensure responsible AI practices. The role requires expertise in Python, ML/DL, and Generative AI, with experience in LLMs and RAG, plus cloud platforms (Azure, Databricks).

Qualifications

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or related quantitative discipline.

Responsibilities

• Design, develop and deploy Machine Learning, Deep Learning and Generative AI solutions to address business challenges.
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Skills

Machine Learning

Deep Learning

Generative AI

Python

LLMs

MLOps

RAG

API integration

Data visualization

Problem solving

Education

Master’s degree in Data Science, Statistics, Mathematics, or related field

Tools

Azure

Databricks

Job description

Job Description

Job title: DATA SCIENTIST

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.

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.

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