- Company Name
- Rexel
- Job Title
- CDI - Data Scientist Confirmé H/F
- Job Description
-
**Job Title**
Confirmed Data Scientist (M/F)
**Role Summary**
As a senior Data Scientist in the AI Solutions & Data Science team, you will translate business challenges from multiple departments (Commerce, Pricing, Marketing, Digital, Supply Chain, IT) into end‑to‑end AI and generative AI solutions. You will assess data readiness, build predictive and prescriptive models, prototype and industrialise models, integrate them with corporate systems, and monitor performance against business KPIs.
**Expectations**
- 2‑4 years of professional data science experience
- Engineering or Master’s level in Data Science, ML/DL, Generative AI, Statistics, or Operations Research
- Fluent in English; French language a plus
**Key Responsibilities**
- Analyse internal stakeholder needs, validate ROI, and assess feasibility (quality, cost, schedule).
- Source, clean, and qualify data; conduct exploratory, descriptive, predictive, and prescriptive analyses.
- Build and tune supervised and unsupervised ML/DL models; design and implement generative AI (LLMs, RAG, agentic AI) solutions via OpenAI APIs.
- Execute full project life cycle: exploration, prototyping, pilot deployment, industrialisation, production run, and continuous improvement.
- Integrate models with enterprise systems (CRM, ERP, webshop, etc.).
- Define and track data‑science KPIs; conduct A/B testing and performance measurement.
- Produce high‑quality code, unit tests, CI/CD pipelines, and documentation.
- Communicate results and progress to technical and non‑technical stakeholders.
- Stay current with AI trends and evaluate new tools for business value.
**Required Skills**
*Technical* – Supervised & unsupervised ML, deep learning frameworks (TensorFlow, PyTorch), generative‑AI techniques (LLMs, RAG, agents), Python programming (scikit‑learn, pandas, NumPy), SQL database querying, data visualization (Matplotlib, Seaborn, Plotly), Flask/FastAPI, CI/CD pipelines, Git.
*Cloud* – Experience with Azure, GCP, or AWS environments.
*Soft* – Strong analytical and problem‑solving capabilities, clear communication, autonomy, rigor in coding practices, teamwork, agility in adapting communication style, and passion for practical, impact‑driven solutions.
**Required Education & Certifications**
- Bachelor or Master (or higher) in Engineering/Data Science, Machine Learning, Statistics, Operations Research, or related field.
- Relevant certifications (e.g., Microsoft Certified: Azure Data Scientist Associate, Google Cloud Professional Data Engineer, or AWS Certified Machine Learning) are an advantage but not mandatory.