Principal Scientist - Data Analytics

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Date: May 6, 2019

Location: Slough, Berkshire, GB

At UCB everything we do starts with a simple question: “How will this make a difference to the lives of people living with severe diseases?” We do that by connecting with patients and their families around the world living with the physical and social burdens of severe disease of the immune system and the central nervous system. Those connections offer new perspectives, drive innovation, and offer the hope of a new generation of therapies that will help to transform lives.

 

Role overview

You will be part of a highly motivated, multi-disciplinary team driven by a passion to improve decision making in Drug Discovery and Development by leveraging advanced data science methods. The Data Science Enablement team is part of R & D Informatics, supporting both early and late development projects and with a wide range of expertise such as the analysis / interpretation of -omics datasets, Artificial Intelligence (including Machine Learning), Data Mining and visualization methods.

 

The advertised role is responsible for developing innovative data science based solutions in the field of target & drug discovery including drug safety assessments. Relevant data types include various omics, functional screening (flow cytometry, imaging), clinical and Real World Evidence data.

 

Primary responsibilities

  • implementation of data science based solutions for relevant questions in Drug Discovery across the entire UCB research portfolio
  • enablement or development of innovative data science techniques
  • communication of scientific results inside and outside the team with all relevant stakeholders
  • Active support of younger scientists in the team
  • Contribution of specific methodological expertise to colleagues in R & D Informatics and in other teams
  • Fostering of collaboration and managing of relevant stakeholders (including IT, management, life scientists and physicians) across the entire company within projects

 

Essential requirements

Candidates must hold a PhD (or have equivalent experience) in bioinformatics / computer science / applied mathematics with skills in the following areas:

  • Considerable experience in Data.
  • Science.Strong scientific leadership combined with flexibility, genuine intellectual curiosity, ideation and eagerness to contribute are key elements of the position.
  • Demonstrable experience and passion for machine learning, data mining and data visualization, preferably applied to biomedical analytical problems with excellent knowledge of the main data types used in biopharmaceutical R&D.
  • Excellent understanding of Drug Discovery concepts, knowledge of life science and medicine and a passion to see the results of your work improving the lives of patients.
  • Deep theoretical understanding and real hands-on experience with a wide range of supervised and unsupervised machine learning methods, including e.g. gradient boosting, Random Forests, variational autoencoders, convolutional neural networks. Additional knowledge of Bayesian Networks and Bayesian inference techniques (e.g. belief propagation, likelihood weighting) would be beneficial.
  • Strong practical experience with deep learning frameworks (e.g. TensorFlow). Additional experience with high performance cloud computing services (e.g. Amazon AWS) would be beneficial.
  • Deep technical knowledge of relevant scripting and analytics software, including R and Python and condidence in programming in a Linux / HPC environment, including shell scripting (bash, tcsh). Additional knowledge of C++ would be beneficial.
  • Excellent communication skills to ensure alignment between computational and life scientists, physicians as well as management.
  • Experience with guiding project teams and/or supervising younger scientists.


Job Segment: Data Analyst, Biotech, Analytics, Database, Scientific, Data, Science, Engineering, Management, Technology

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