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Analytics Solutions Manager

Lonza

Skills

Required

  • data science
  • modelling
  • forecasting
  • Python
  • data analytics
  • portfolio management tools / decision-support applications
  • machine learning / AI-based
  • analytical solutions
  • Plotly
  • Dash
  • Docker
  • Microsoft Azure

Preferred

  • analytical product ownership
  • advanced analytics
  • modelling development
  • scenario modelling

Market Modelling team develops forecasting models, analytical products and decision-support tools that help Lonza make better strategic, portfolio and commercial decisions in an uncertain environment. We are looking for a technically proficient Analytics Solutions Manager to drive the development, adoption and continuous evolution of analytical products supporting stakeholders across Commercial, Strategy, Business Development, Portfolio Management and Marketing functions. In this role, you will own and develop a portfolio of analytical applications and decision-support tools, acting as the bridge between business stakeholders and analytical development. You will ensure our products address meaningful business questions, deliver measurable value and evolve in line with changing business needs.

About Lonza

  • Lonza At Lonza, our people are our greatest strength.
  • With 30+ sites across five continents, our globally connected teams work together every day to manufacture the medicines of tomorrow.
  • Our core values of Collaboration, Accountability, Excellence, Passion and Integrity reflect who we are and how we work together.
  • Everyone’s ideas, big or small, have the potential to improve millions of lives, and that’s the kind of work we want you to be part of.
  • Innovation thrives when people from all backgrounds bring their unique perspectives to the table.
  • At Lonza, we value diversity and are committed to creating an inclusive environment for all employees.
  • If you’re ready to help turn our customers’ breakthrough ideas into viable therapies, we look forward to welcoming you on board.

Ready to shape the future of life sciences?

Apply now.

Responsibilities

  • This is a hands-on, cross-functional role combining analytical product ownership, stakeholder engagement, advanced analytics and modelling development.
  • Own and develop a portfolio of analytical products and decision-support tools, from concept through deployment, adoption and continuous improvement
  • Partner with stakeholders to understand business challenges and translate them into analytical solutions
  • Drive product adoption, gather feedback, prioritize enhancements and ensure products continue to deliver business value
  • Perform advanced analyses, forecasting and scenario modelling to support strategic, portfolio management and commercial decisions
  • Collaborate with data scientists, engineers and business teams to develop and deliver robust, user-friendly analytical solutions
  • Identify new opportunities where modelling and analytics can create value

Requirements

  • Strong analytical skills, structured problem-solving and business curiosity
  • Demonstrated ability to translate business needs into analytical solutions and drive them through development and delivery
  • Experience applying data science, modelling and forecasting techniques to real-world business problems
  • Ability to engage and influence stakeholders across multiple functions and organizational levels Hands-on experience in Python for data analytics and modelling
  • Excellent communication and presentation skills

Curious, proactive and comfortable working in ambiguous environments

  • The ideal profile will also include several of the following: Experience owning, developing and/or supporting data analytics products, portfolio management tools or decision-support applications
  • Experience in pharmaceuticals, biotechnology, manufacturing or related industries

Experience with machine learning or AI-based analytical solutions

  • Experience with data visualization, dashboarding or analytical application development (e.g., Plotly Dash, Streamlit) Familiarity with software engineering practices for analytical applications, including
  • Git, testing, containerization (e.g., Docker) and CI/CD Exposure to MLOps, ML pipeline operationalization, cloud platforms (ideally Microsoft Azure), or the deployment and monitoring of analytical applications

Analytics Solutions Manager Location

Basel, Switzerland.