Senior / Principal Data Scientist

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Organisation
Eagle Genomics
Locations

London / Cambridge

Application Deadline

This is your opportunity to join a pioneering company working at the intersection of two exciting areas: life sciences and data science. We’re at the centre of the digital reinvention of life sciences R&D, using the latest technologies to enable data-driven discovery.

As we plan for ambitious, accelerated growth, we have expanded our network of offices in technology and innovation hubs around the world: in the UK, Germany, India, the US, France, and Ukraine. So, the stage is set to make great steps forward.

Department: Data Science

Permanent – Full Time

Location: United Kingdom - Flexible remote working with occasional travel into either the London or Cambridge office, as well as some travel to Eagle’s European offices.

The Job:

We are looking for a broad level of experience: from senior data scientists to principal data scientists with many years of commercial and/or academic experience.

  • You will work jointly with scientists, bioinformaticians and data/software engineers to make sense of a variety of data sources.
  • You need the capacity to analyse large amounts of data, build predictive models and machine-learning algorithms and generalise such models into packageable and reusable data science tools.
  • The ability to innovate, abstract and create is key.
  • You will work with complex, meshed, and hyper-dimensional data, combine modelling techniques, and generalise them.

Requirements

Essential:

  • Strong programming experience in either R or Python.
  • Working knowledge of Linux
  • Proven track record in analysing and interpreting large data sets and statistical analysis
  • Degree in relevant fields such as statistics, computer science, computational biology, etc.
  • Solid knowledge of machine learning and deep learning techniques
  • Highly organised with a meticulous attention to detail.
  • The ability to communicate clearly and effectively with specialists from your own and other fields
  • A Ph.D. degree is not required but preferred.

Experience in at least one of the following domains:

  • Natural Language Processing
  • Bioinformatics, Biostatistics or Genetics
  • Graph-based methods and knowledge graph analysis and inference
  • Causal analysis and inference

Nice to have:

  • Industrial experience working with a multidisciplinary team
  • Publications in academic setting and patents in commercial setting

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