Data Scientist

Intro Summary of the Role

The Data Scientist is a Bioscience-specific role responsible for developing, deploy, and improve data science, machine learning, and AI solutions that solve business problems and create measurable value through predictive and prescriptive analytics, forecasting, intelligent automation, and decision-support systems.

This role works across the Azure/Fabric platform to develop scalable and practical data science and AI solutions, combining data analysis, model development, deployment, and continuous improvement. The role operates at a hands-on professional level, balancing technical delivery with experimentation, solution design, and stakeholder engagement.

The role works closely with business, technology, and data teams to ensure data science and AI capabilities are practical, secure, maintainable, and aligned to business priorities.

What You Will Get

• An agile career and dynamic working culture.
• An inclusive and ethical workplace.
• Compensation programs that recognize high performance.
• A variety of benefits dependent on role and location.

The full list of our global benefits can be found here: https://www.lonza.com/careers/benefits.

What You Will Do

• Develop and deliver end-to-end data science, machine learning, and AI solutions aligned to business needs, incorporating exploratory analysis, predictive and prescriptive analytics, and insight generation.
• Design and build predictive, recommendation, forecasting, optimization, and decision-support systems that improve business performance, operational efficiency, and strategic decision-making.
• Develop and apply machine learning models to solve complex business problems and generate measurable outcomes across customer, commercial, and operational domains.
• Work with diverse data sources to create reliable, well-structured datasets that enable high-quality analytics and AI solutions.
• Design and execute feature engineering, model development, evaluation, and experimentation approaches to ensure robust, reliable, and high-performing models.
• Develop and deploy scalable machine learning and AI solutions on Azure, ensuring security, maintainability, and production readiness.
• Build and integrate data products, APIs, and AI services that enable consumption of analytics and machine learning capabilities across the business.
• Design and deliver LLM-based applications, retrieval-augmented generation (RAG) systems, and agentic AI workflows that coordinate tools, data sources, and APIs to support complex decision-support use cases.
• Own the monitoring, evaluation, and continuous improvement of models and AI systems in production, including performance, drift, cost, and business impact.
• Translate business problems into analytical and AI-driven solutions, working closely with stakeholders to define requirements and delivery approaches.
• Communicate insights, recommendations, and technical concepts clearly to both technical and non-technical audiences.
• Apply responsible AI, governance, security, and engineering best practices to ensure solutions are explainable, compliant, and maintainable solutions.

What We Are Looking For

• Python, SQL, and Git
• Azure cloud
• Machine learning and statistical modelling (forecasting, classification, clustering, recommendation systems, optimization, experimentation)
• Azure Machine Learning and Azure AI services, including MLOps (deployment, CI/CD, monitoring, drift detection, retraining)
• Generative AI / LLM applications (RAG and agent-based workflows)
• API development for deploying ML/AI solutions and integrating services
• Enterprise data experience (e.g., CRM, ERP, operational data) and data visualization (e.g., Power BI)