Lead Data Scientist

Bring more to life.

At Danaher, our work saves lives. And each of us plays a part. Fueled by our culture of continuous improvement, we turn ideas into impact, innovating at the speed of life.

Our 60,000+ associates work across the globe at more than 15 unique businesses within life sciences, diagnostics, and biotechnology.

Are you ready to accelerate your potential and make a real difference? At Danaher, you can build an incredible career at a leading science and technology company, where we're committed to hiring and developing from within. You'll thrive in a culture of belonging where you and your unique viewpoint matter.

DHR Enterprise AI Solutions is Danaher's enterprise AI engineering capability, responsible for identifying opportunities, building and scaling reusable AI solutions, and accelerating measurable business impact across operating companies. We combine product, architecture, AI science, engineering and operations to industrialise AI, establish enterprise standards and enable the next generation of AI-powered products, workflows, applications and decision-making.

We look forward to welcoming you to our organisation.

In DHR Enterprise AI Solutions, you will be responsible for creating reusable, production-grade Data Science, Machine Learning and AI solutions that solve complex business, scientific, laboratory and instrument-related challenges across Danaher.

You will serve as a technical expert in Data Science and Machine Learning, helping transform data into predictive capabilities, optimisation models, actionable insights and intelligent decision-support solutions that can be deployed, scaled and reused across operating companies.

This is a Danaher Corporate role, hosted by our Cytiva operating company in Kraków, and will be an on-site role (Kraków).

In this role, you will have the opportunity to:

• Develop advanced statistical, data science, machine learning and AI models that solve complex business and scientific problems and generate measurable impact across Danaher operating companies.
• Design and lead experiments, evaluation frameworks, validation methodologies and performance benchmarks that ensure scientific rigour, model reliability and evidence-based decision making.
• Curate, transform and analyse enterprise data assets, establishing high-quality datasets, feature sets and analytical foundations that accelerate machine learning, optimisation and predictive modelling initiatives.
• Select, develop and refine appropriate modelling approaches, algorithms and analytical techniques, providing technical leadership across the full model-development lifecycle from experimentation through production deployment.
• Partner with Product Owners, Architects, AI Scientists and Engineers to integrate analytical capabilities, predictive models, forecasting solutions and optimisation techniques into scalable, production-ready enterprise solutions.

The essential requirements of the job include:

• Strong expertise in statistics, machine learning, predictive modelling, optimisation techniques and quantitative analysis, gained through hands-on delivery of Data Science and Machine Learning solutions.
• Deep understanding of experimental design, hypothesis testing, Bayesian inference, causal inference, model evaluation, feature engineering, forecasting methodologies and analytical best practices.
• Proficiency in Python, SQL, notebooks, cloud-based analytics platforms and modern machine learning frameworks used to develop, train and deploy production-grade models.
• Strong analytical and problem-solving skills, with the ability to frame ambiguous business or scientific challenges and develop data-driven solutions that create measurable value.
• Excellent communication and stakeholder-management skills, with the ability to explain complex analytical concepts and influence both technical and business audiences.

It would be a plus if you also possess previous experience in:

• Developing predictive models, optimisation capabilities, forecasting solutions or advanced analytics that improve operational performance, scientific outcomes, customer experience or business results.
• Building machine learning solutions using techniques such as gradient boosting, ensemble methods, Bayesian modelling, time-series forecasting, optimisation algorithms or other advanced statistical approaches.
• Working in life sciences, diagnostics, healthcare, laboratory environments, advanced manufacturing or other data-rich scientific industries.

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Join our winning team today. Together, we’ll accelerate the real-life impact of tomorrow’s science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life.

For more information, visit www.danaher.com.