Data Scientist (m/f/d)

AI · Data Science

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Your tasks

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, 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 the key business stakeholders involved in the projects 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.
Defining business requirements, Document them, create wire frame, Communicate to Developers, Monitor Development, conduct internal testing and validate every KPI Numbers & Formulas.
Own and develop relationship with partners, working with them to optimize and enhance our integration.
Report on common sources of technical issues or questions and make recommendations to product team.
Communicate key insights and findings to product team.

4+ years of prior experience in a Data Scientist role.
Strong Data Engineering skills and software development skills.
Expertise in Python and any one of the associated frameworks (scikit-learn, Tensorflow, 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 experience in production.
Excellent communication and collaboration skills, able to explain complex effects and impacts in simple business terms.
Knowledge of optimization techniques (OR, MIP, …) is a plus.
Knowledge on 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.
Flexible working schedule.

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, 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 the key business stakeholders involved in the projects 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.
Defining business requirements, Document them, create wire frame, Communicate to Developers, Monitor Development, conduct internal testing and validate every KPI Numbers & Formulas.
Own and develop relationship with partners, working with them to optimize and enhance our integration.
Report on common sources of technical issues or questions and make recommendations to product team.
Communicate key insights and findings to product team.

4+ years of prior experience in a Data Scientist role.
Strong Data Engineering skills and software development skills.
Expertise in Python and any one of the associated frameworks (scikit-learn, Tensorflow, 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 experience in production.
Excellent communication and collaboration skills, able to explain complex effects and impacts in simple business terms.
Knowledge of optimization techniques (OR, MIP, …) is a plus.
Knowledge on 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.
Flexible working schedule.