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Location

Poissy, Yvelines | France

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Job description

Your role is to leverage data and advanced analytical techniques to extract insights, solve complex problems, and drive data-driven decision-making within an organization. You will BE part of Generative AI CoE building LLM, foundation models and structuring AI projects, collaborating with cross-functional teams to uncover patterns, develop predictive models and deliver actionable recommendations. As a senior member of the team, you will provide technical leadership, mentorship and contribute to the overall data science strategy

Key Responsibilities
Data Analysis and Modeling - Apply statistical analysis, machine learning and data mining techniques to analyze large and complex datasets. Clean, preprocess and transform raw data into usable formats. Develop and implement predictive models, algorithms and statistical methodologies to derive actionable insights and make accurate predictions.
Advanced Analytics and Visualization - Utilize advanced analytics tools and techniques to explore and visualize data, identify trends and discover patterns. Develop interactive dashboards and data visualizations to effectively communicate complex findings to stakeholders
Problem Solving and Strategy - Collaborate with business stakeholders to understand their challenges and requirements. Formulate data-driven solutions and strategies to address complex problems and support business objectives. Translate business problems into analytical frameworks and identify opportunities for leveraging data science
Model Development and Deployment - Design, develop and implement advanced machine learning models and algorithms. Optimize and fine-tune models for performance, accuracy and scalability. Collaborate with software engineers to deploy models into production environments and ensure their integration with existing systems
Team Leadership and Mentorship - Provide technical guidance and mentorship to junior data scientists. Review and provide feedback on their work, ensuring adherence to best practices and quality standards. Contribute to the hiring and onboarding of new team members
Collaboration and Communication - Collaborate with cross-functional teams, including data engineers, business analysts and stakeholders from various departments. Communicate complex analytical concepts and findings to both technical and non-technical audiences. Work with stakeholders to define project goals, scope and success criteria
Continuous Learning and Research - Stay updated with the latest advancements in data science, machine learning and related fields. Explore new methodologies, algorithms and tools to enhance the organization's data science capabilities. Contribute to research and development initiatives, publish papers and participate in relevant conferences or industry events
Data Governance and Ethics - Ensure compliance with data governance policies, security protocols and privacy regulations. Uphold ethical standards in data handling, modeling and decision-making - University degree in computer science, data science, statistics, mathematics, artificial intelligence, or a related field. Advanced degree is desirable (Master's or Ph.D.)
- Strong academic background in data science or machine learning is preferred.
- Extensive experience (5+ years) in data analysis, predictive modeling, and statistical analysis. Proven track record of delivering data-driven solutions and generating actionable insights.
- Proficiency in programming languages such as Python or R. Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).
- Deep understanding of statistical analysis, machine learning algorithms, and data mining techniques. Familiarity with both supervised and unsupervised learning approaches.
- Experience with data visualization tools and techniques (e.g., Tableau, Power BI) to communicate complex findings effectively.
- Strong problem-solving skills and the ability to translate business requirements into analytical solutions.
- Leadership abilities, with experience in guiding and mentoring junior team members.
- Excellent communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders.
- Knowledge of big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is a plus.
- Background on Large Language Models and Foundation Models for Generative AI applications.
- Strong attention to detailand ability to work with large and complex datasets.
- Strong project management skills, including the ability to prioritize tasks, meet deadlines, and manage multiple projects simultaneously.
- Continuous learning mindset and a passion for staying updated with the latest trends and advancements in data science and machine learning.

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At Stellantis, we assess candidates based on qualifications, merit and business needs. We welcome applications from people of all gender identities, age, ethnicity, nationality, religion, sexual orientation and disability. Diverse teams, will allow us to better meet the evolving needs of our customers and care for our future.

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