Senior Data Scientist

About the Company

Responsibilities

• ● Initial focus will be on automating forecasting and scenario simulation processes for Sales, Finance, and Commercial Support; future scope may extend to other CBS functions.
• ● Identify further business problems across Purchasing, Finance, Logistics, Sales Administration, and Personnel that can be solved through statistics, machine learning, or AI.
• ● Collect, clean, and prepare large structured and unstructured datasets; run exploratory data analysis to uncover patterns, trends, and business opportunities.
• ● Develop, train, validate, and optimize machine learning models for predictive and prescriptive analytics.
• ● Build and maintain data science solutions using Databricks and Azure ML Studio, collaborating with Data Engineers to prepare data, develop features, and industrialize analytical and machine learning use cases.
• ● Deploy and monitor machine learning models in production, evaluating performance with appropriate statistical metrics and retraining as needed.
• ● Communicate analytical findings and forecast outputs to technical and non-technical stakeholders, including Sales and Finance leadership, through clear visualizations and presentations.
• ● Support AI-driven process automation by integrating predictive models into business workflows, working cross-functionally to keep solutions aligned with business goals.
• ● Document models, assumptions, methodologies, and analytical processes according to company standards.
• ● How You'll Work :
• ● Stakeholder Communication
• ● Translate complex business data into actionable insights and forecast recommendations for Sales, Finance, and commercial support teams.
• ● Explain model and forecast performance, assumptions, and limitations clearly to both technical and non-technical audiences.
• ● Model Governance & Data Quality
• ● Build reliable, interpretable models, and monitor for concept drift or performance degradation as forecast cadence increases.
• ● Ensure reproducibility through version control, documentation, and experiment tracking.
• ● Apply company standards for data quality, security, privacy, and governance, validating data sources before model development.
• ● Continuous Learning & Collaboration
• ● Stay current with advances in data science, AI, and machine learning, and bring new ideas to the team.
• ● Share knowledge with colleagues through documentation, code reviews, and mentoring.

Requirements

• ● -5 years of experience as a Data Scientist, Machine Learning Engineer, or in a similar analytical role.
• ● Hands-on experience with Databricks and PySpark for scalable data processing, and strong Python programming skills (including Pandas, NumPy, and scikit-learn) for developing, training, and evaluating machine learning models.
• ● Good knowledge of machine learning techniques, including regression, classification, clustering, recommendation systems, time-series forecasting, and anomaly detection.
• ● Solid understanding of statistics, probability, hypothesis testing, and experimental design.
• ● Strong SQL skills for querying, transforming, and analyzing large datasets.
• ● Nice to Have
• ● Exposure to LLMs, GenAI, or AI agent workflows.
• ● Power BI or similar for communicating insights to stakeholders.
• ● Background in FP&A, demand planning, or a Global Business Services / Shared Services environment.
• ● Bachelor's or Master's degree in a quantitative field (Computer Science, Statistics, Mathematics, AI, or related).
• ● In Michelin we offer:
• ● Hybrid way of working;
• ● A customizable benefits package with options to choose: gym access, medical or dental services, private retirement pension, deduction of public transport costs, cultural activities vouchers etc.
• ● Private medical subscription;
• ● Life insurance;
• ● Lunch vouchers and discounts;
• ● Deduction of vacation costs.
• ● How we recruit:
• ● Once you submit your application, one of our recruiters reviews it. If your profile fits our role:
• ● We have a phone call to get to know each other;