- Company Name
- CADREMPLOI
- Job Title
- Lead Data Scientist F/H
- Job Description
-
**Job Title**
Lead Data Scientist
**Role Summary**
Strategic leader responsible for designing, developing, and industrializing AI/ML models that drive business value across retail operations. Oversees the formation and scaling of the Data Science team, establishes methodological standards, and collaborates with cross‑functional stakeholders to embed data‑driven solutions throughout the organization.
**Expectations**
- Deliver end‑to‑end AI solutions for sales forecasting, credit scoring, churn detection, inventory optimization, and asset valuation.
- Build and maintain a high‑performing Data Science team (2‑3 members).
- Ensure model quality, scalability, and seamless integration with production pipelines.
- Act as the primary liaison between Data Science, Engineering, Analytics, and business units.
- Lead continuous innovation and propose high‑impact AI use cases.
**Key Responsibilities**
- Define project scope, design, and implement machine‑learning models aligned with business needs.
- Industrialize models using MLOps best practices (MLflow, Docker, Airflow, CI/CD, monitoring).
- Set methodological standards, coding guidelines, and documentation for the Data Science function.
- Recruit, mentor, and develop junior Data Scientists, fostering skill growth.
- Collaborate with Data Engineering, Data Quality, and domain teams (Marketing, Retail, Finance, HR) to ensure data availability and model adoption.
- Conduct technology scouting, evaluate emerging AI tools, and recommend enhancements to the tech stack.
**Required Skills**
- Advanced Python programming and SQL proficiency.
- Experience with machine‑learning frameworks (TensorFlow, PyTorch).
- Strong MLOps knowledge (MLflow, Docker, Airflow, CI/CD pipelines).
- Hands‑on experience with cloud platforms and data warehouses (e.g., Snowflake).
- Proven ability to lead and grow technical teams.
- Excellent communication skills; capable of translating complex AI concepts for non‑technical audiences.
**Required Education & Certifications**
- Master’s degree (or equivalent) in Applied Mathematics, Statistics, Machine Learning, Computer Science, or related quantitative field (Bac+5).
- Relevant certifications in data science, machine learning, or cloud platforms are a plus.