Data Scientist

Department Mission:
The modelling team's goal is to transform data into valuable and actionable insights that contribute to improving the organization's performance and profitability. To achieve this, the team collaborates closely with various internal departments (Sales, Marketing, Risk, Finance, HR, Compliance, etc.) and international partners.

As a Data Scientist within the modelling team, you will apply advanced statistical and machine learning methods to extract insights from internal and external data. You will test hypotheses, build predictive models, and develop decision-support tools tailored to specific business needs.

• Develop and evaluate predictive models and algorithms, ensuring compliance with the AI Act.

• Build and implement statistical models in collaboration with internal and external partners.

• Segment the customer base to improve marketing campaign efficiency and overall profitability.

• Develop customer insights to minimize risks such as fraud and non-compliance.

• Ensure proper documentation and optimal use of developed models across teams.

• Combine internal, external, and digital data to solve specific business problems or support strategic decisions.

• Present analytical results and insights clearly to non-technical stakeholders.

• Stay up to date with trends and innovations in Data and AI.
  
  

Skills and Competencies:

• Strong analytical mindset with the ability to translate business problems into quantitative solutions.

• Excellent verbal and written communication skills.

• Ability to explain complex analytical results to non-technical audiences.

• Strong project management and stakeholder collaboration skills, with a focus on meeting deadlines.

• Precise in documentation and transparent about development and implementation steps.

• Team-oriented, open-minded, creative, and curious.

Education and Experience:

• Master's or PhD in Mathematics, Statistics, Cognitive Sciences, Engineering, or equivalent experience.

• Proficiency in programming languages such as Python, SQL, and SAS.

• Experience with machine learning models (e.g., regression, random forest, XGBoost).

• Knowledge of text analytics or big data technologies (e.g., noSQL).

• Proficient in Microsoft Office Suite (Excel, Word, PowerPoint).

• Fluent in French and English; knowledge of Dutch is an asset.