Your tasks
- Lead AI engagements and be the main responsible for project delivery
- Manage key project stakeholders (technical and non technical) on project delivery and for future opportunities
- Prepare and lead software architecture and design discussions
- Review team design decisions and guarantee high quality code
- Navigate uncertain projects with poor scope and task definition, bring structure and organization
- Push for business impact and value delivery
- Bring expertise on Machine Learning AI agents to automate business workflows, propensity modelling to roll out marketing campaigns, forecasting for demand prediction and assortment optimization.
- Present to technical and or business stakeholdersPrepare 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.
- Respond to Ad-Hoc business analysis and conduct Business analytics using SQL complex queries.
What do we expect from you?
- 2+ years of demonstrable experience leading teams, being accountable for end to end project delivery and responsible for planning, assigning tasks and growing other team members.
- 4+ years of prior experience in a Data Scientist role as an individual contributor
- Demonstrable architecture and software design knowledge
- Strong Data Engineering 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
What you can expect
- 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.
- 23 vacation days + 24 & 31 December.
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