Data Scientist

Mid-level
🇪🇸 Spain
Data Scientist
Data science & Analytics

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.

Lonza in Porriño, Spain is looking for an experienced Data Scientist to join our Manufacturing Science and Technology (MSAT) team. As our Data Scientist, you will be responsible for developing real time process monitoring tools and analytics used for fault detection as well as prediction. This individual will be required to execute the efficient exploration and interpretation of complex data-sets by constructing statistical models to summarize and explain process variability and equipment anomalies. He or she will interface daily with Process Experts to mine, clean and explore data sets used to identify causal factors as well as potential opportunities to predict ideal process outcomes, optimize timing of critical events, process productivity, product quality, and general process knowledge. The role will be required to identify and apply appropriate modeling or statistical techniques suitable to unique problem statements.

Key responsibilities:

  • Owner locally of the Lonza Global Databa base and associated systems, and their maintenance in Lonza Porriño.
  • Participate in the investigation of both basic and complex process events and anomaly investigation.
  • Collaboration with Global teams in strategic projects and implementation of global policies in Lonza Porriño.
  • Develop automated predictive process monitoring tools and systems.
  • Data analysis via “standard” methods, e.g. Regression Analysis, Clustering Analysis, Dimensionality Reduction Analysis.
  • Perform Data mining, cleaning and data-set prep in order to execute complex multivariate statistical analysis (MVA).
  • Develop and apply AI and Machine Learning (ML) to applications of data mining, prescriptive analytics, process monitoring.
  • Works with Technical teams to support data collection, virtualization and integration.
  • Be proactive and bring initiatives to the team, both for the quality of the analysis and for finding efficiencies on a day-to-day basis.

Key requirements:

  • Masters of Science degree in Statistics or Data Science required. The ideal candidate will also have a background in Biology and Bioprocess Engineering.
  • Demonstrated understanding of related industrial or bio-pharmaceutical manufacturing processes, data analysis via “standard” methods (e.g. Regression Analysis, Clustering Analysis, Dimensionality Reduction Analysis) with ML/AI expertise.
  • Experience in manipulating / managing complex data-sets, Oracle and SQL database querying/manipulations, Multi-Variant Analysis testing and optimization, Extract Transform Load tools.
  • Excellent written and verbal communications skills to document relevant findings and investigational process in clear structured manner are required.
  • Natural sciences background a plus.
  • C, C++, SAS, MatLab, Minitab, SPSS, Statistica, PowerBI, SeeQ, SVB, T-SQL.

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.

 

NL Synaffix B.V.

NL Synaffix B.V.

Company focuses on providing best-in-class ADC technologies for various applications, including immune-oncology and targeted gene therapy.

Biotechnology
Healthcare
Pharmaceuticals
Research and Development (R&D)

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