Senior Health Data Scientist

At Fresenius Medical Care, we are the global leader in kidney care, committed to improving the lives of patients with chronic kidney disease. Our mission is to deliver high-quality, innovative products, services, and care across the entire healthcare journey. we work with purpose and compassion, supported by a global team of over 110,000 employees.

Within our Care Enablement segment, we develop and provide life-sustaining medical products, digital health solutions, and therapies that empower clinical teams and improve patient outcomes. Our FME Reignite strategy drives transformation through innovation, efficiency, and sustainable growth.

We Commit to doing things the right way— growing with purpose and leading kidney care with integrity and innovation

As a Center of Excellence, Commercial Business Services (CBS) drives commercial excellence across Care Enablement. The team delivers market insights, health economics expertise, brand management, and validated marketing and sales strategies. CBS leads the development of commercial tools, processes, and training to support market access, strategic product positioning, and enhance the global customer experience. Join our passionate team and help shape healthcare worldwide!

As the Senior Data Scientist, Predictive Analytics & Modeling you design, develop and scale advanced predictive analytics and machine learning models that support commercial decision-making and drive business growth. By transforming complex commercial, pricing, financial, and customer data into actionable insights, the role enables pricing optimization, tender success, forecasting accuracy, opportunity identification, and sales effectiveness. Working closely with cross-functional stakeholders, the Senior Data Scientist ensures analytical solutions are embedded into business processes, continuously improved, and deliver measurable commercial impact through data-driven decision-making.

Develop predictive analytics and machine learning solutions using CRM, ERP, finance, pricing, and commercial data to address complex business challenges

Build, validate, and optimize models for forecasting, pricing, customer behavior analysis, opportunity identification, and strategic decision-making

Lead the full model lifecycle, including problem definition, data preparation, feature engineering, validation, deployment, monitoring, and continuous improvement

Ensure analytical solutions are accurate, scalable, interpretable, and aligned with responsible data practices

Develop pricing, profitability, and tender analytics models, including price elasticity, discount optimization, profitability simulations, and win/loss analysis

Identify commercial growth opportunities through dynamic pricing, cross-/upsell propensity modeling, and analysis of customer, product, market, and sales behaviors

Evaluate tender data and requirements to identify trends, risks, pricing opportunities, and bid improvement areas

Partner with Commercial, Marketing, Finance, IT, and other stakeholders to embed analytics into business processes and decision-making

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, Engineering, Business Analytics, Business Administration, or a related quantitative field

• 5+ years of experience in data science, predictive analytics, machine learning, statistical modeling, or related analytical roles, ideally within MedTech, healthcare, life sciences, high-tech manufacturing, or other complex commercial environments
• Demonstrated success in developing predictive models that deliver measurable commercial outcomes and business value
• Strong experience working with complex datasets from CRM, ERP, finance, pricing, and commercial systems, applying advanced analytical and machine learning techniques to solve business challenges
• Experience in pricing analytics, forecasting, optimization, profitability analysis, and commercial decision support is highly desirable
• Proven ability to communicate complex analytical concepts and model results to both technical and non-technical stakeholders, driving data-informed decision-making
• Proficient in Python, R, SQL, and data analytics environments, with experience using BI and visualization tools such as Power BI or similar platforms
• Knowledge of data governance, data security, and compliance requirements, with experience developing scalable analytical solutions in complex data environments
• Fluent in English, both written and spoken; Individual opportunities for self-determined career planning and professional development

The benefits of a successful global corporation with the collegial culture of a medium-sized company

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