SENIOR DATA SCIENTIST

The Senior Data Scientist & Business Partner designs and delivers end-to-end data science solutions that improve commercial decision-making. You work hands-on from data and solution design through modelling, validation and productionization, while acting as the Data Science partner for a business line and ensuring the solutions translate into measurable business value.

• Design end-to-end data science solutions from business problem through data requirements, modelling approach, validation, deployment and business integration

• Build and deliver robust decisioning and predictive models ready for production use, including propensity, churn, customer value, segmentation, forecasting and next-best-action use cases

• Define features, target variables, model outputs and analytical datasets, working hands-on with Python and SQL and with Data Engineering where production data assets are required

• Validate model performance and business impact through robust statistical methods, experimentation and appropriate controls

• Operationalize models with Data Engineering and MLOps, integrate their outputs into CRM, campaigns and other business decision processes, and remain accountable for model performance once in use, driving recalibration where needed

• Act as the Data Science partner for a business line: understand its strategy and economics, identify high-value analytical opportunities, and translate results into concrete decisions and measurable value

• Master’s degree or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering or another highly quantitative field

• 7+ years of professional Data Science experience, with a strong track record designing and delivering end-to-end analytical solutions and models into production

• Advanced Python and SQL, with strong foundations in statistics, machine learning and experiment design and sound engineering practices including version control, testing and code documentation

• Proven hands-on across the full model lifecycle: feature engineering, target definition, model validation, deployment, monitoring and recalibration

• Strong solution-design capability, translating complex business requirements into data, modeling and decisioning solutions that can be operationalized in business processes

• Hands-on experience in a modern cloud Data Science / ML environment, ideally Microsoft Fabric and Azure Machine Learning or equivalent

• Strong business partnering and stakeholder management skills

• Experience in customer / commercial analytics, CRM and decisioning or financial services, including exposure to model governance and explainability

• Fluency in English for collaboration with teams and management in Switzerland