Data Scientist; m​/f​/d

Responsibilities

• Hands‑on implementation of Machine Learning use, AI agents to automate business workflows, propensity modelling to roll out marketing campaigns, forecasting for demand prediction and assortment optimization.
• Deploy, maintain, and monitor AI solutions. Design scenarios and schedule jobs to run batch models or APIs for on‑demand serving.
• Present to technical and/or business stakeholders. Prepare and carry out presentations with key business stakeholders to show the results of ML models to a non‑technical audience and how they bring value to the business.
• Gather business requirements from business users and technically implement them to meet the requirements.
• Define business requirements, document them, create wireframes, communicate with developers, monitor development, conduct internal testing, and validate every KPI, numbers and formulas.
• Own and develop relationships with partners, working with them to optimise and enhance our integration.
• Report on common sources of technical issues or questions and make recommendations to the product team.
• Communicate key insights and findings to the product team.

• 4+ years of prior experience as a Data Scientist.
• Strong data engineering skills and software development skills.
• Expertise in Python and any one of the associated frameworks (scikit‑learn, Tensor Flow, PyTorch, H2O, etc.) for ML and DL.
• Expertise in the concepts of Statistics, Machine Learning and Agent‑based AI.
• Knowledge in ML‑Ops (deployment of models, model performance monitoring, data drift, REST API integration, simulations, etc.).
• At least 3 machine learning project implementation experiences in production.
• Excellent communication and collaboration skills, able to explain complex effects and impacts in simple business terms.
• Knowledge of optimisation techniques (OR, MIP, etc.) is a plus.
• Knowledge of Dataiku is a plus.

• Be part of an international and talented team, enjoying an excellent work environment where people are passionate about what they do.
• Attractive salary according to experience and knowledge provided.