Data Scientist

Singapore, Tuas Singapore
Switzerland, Basel
United Kingdom, Slough

Today, Lonza is a global leader in life sciences operating across three continents. While we work in science, there’s no magic formula to how we do it. Our greatest scientific solution is talented people working together, devising ideas that help businesses to help people. In exchange, we let our people own their careers. Their ideas, big and small, genuinely improve the world. And that’s the kind of work we want to be part of.

Growth expectation in Operations and the challenge of significant COGS reduction can only be adequately addressed by applying a new digital, simulation and modelling technologies. Different digital technologies enable an increase of throughput while decrease COGS. This position will identify, initiate, manage and coordinated digital projects and will help creating a prioritised and with the Divisions aligned roadmap to drive significant value from LPNB’s future digitally optimized factories.

In this role, you will apply your practical experience in mining and analyzing structured and unstructured data, your deep understanding of machine learning algorithms, and your willingness to write codes to explore problems and understand data, all while solving challenging real-world problems at different manufacturing scale.

You will interact with key customers in line with Sales & Marketing to address the need for production data analysis and supply chain transparency and will coordinate with R&D, Functional Excellence, Ops sites, and Corporate IT/OT to help addressing customer needs. You will work hand-in-hand with Lonza experts in all different disciplines from Manufacturing, MSAT, R&D to QA&QC, etc. and with experts from academia in a collaborative way, maximizing information generated out of manufacturing data by using established and new “analytical” technologies. You will work in domains ranging from smart manufacturing (reinforcement learning) at small Laboratory scale up to large commercial scales.

Key responsibilities:

  • Collect and assess pain points in production in alignment and collaboration with  Divisions and other internal and external stakeholders and apply new data science, modelling and simulation technologies. 

  • Establish and continuously verify a roadmap for digital data based optimization and define, design, and execute the process to identify and advance significant digital initiatives.

  • Ensure digital program initiatives and PoC (Proof of concept) are linked to Group Operations and Divisional strategies and desired outcomes and metrics.

  • Evaluate the business potential of proposed PoC ensuring selected will provide the highest value for LPBN Ops.

  • Manage projects’ status, progress reporting, risks/issues, scheduling, quality, and continual improvement.

  • Plan/lead program reviews and briefings; identify and report on issues or related problems and potential risks.

  • Create plans and processes required to meet all performance, schedule, quality, cost, and security requirements.

  • Connect digital PoCs with existing target architecture, and proactively communicate with Divisional Operation, Sales & Marketing, functional excellence, Global Engineering/SGI and R&D to ensure no duplication of work and share actively knowledge across LPBN.

Key requirements:

  • Deep Learning, Bayesian Modeling, Natural Language Processing.

  • We also expect you have strong expertise in Python/R, Scala, Java, C/C++

  • Have advanced analytical knowledge of manufacturing data

  • Experience in developing big data analysis

  • Developing and piloting the data models and algorithms

  • Experience in developing enterprise model and executing predictive analytics

  • Experience with SIMCA, CAMO Analytics, Looker, SEEQ is an advantage

  • Capable of acting as both a project manager (understanding of best project management practices) for relevant digital pilots and do data analysis as described above

  • Experience leading digital projects in a changing and growing business environment.

  • Able to connect strategy with action technology and action plans.

  • Able to collaborate and communicate with a variety of stakeholders, ensuring that all stakeholders have appropriate information in a timely manner.

  • Analytical ability to create business case for technologies, and understand where risks may arise.

  • Pharma domain knowledge is a required

  • Good understanding of cGMP requirement and specifically validation requirement.

Every day, Lonza’s products and services have a positive impact on millions of people. For us, this is not only a great privilege, but also a great responsibility. How we achieve our business results is just as important as the achievements themselves. At Lonza, we respect and protect our people and our environment. Any success we achieve is no success at all if not achieved ethically.

People come to Lonza for the challenge and creativity of solving complex problems and developing new ideas in life sciences. In return, we offer the satisfaction that comes with improving lives all around the world. The satisfaction that comes with making a meaningful difference.

Reference: R38833