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Data Scientist

Employer
Barrington James
Location
Oslo (Fylke), Østlandet (NO)
Salary
800,000 NOK
Start date
17 Nov 2023
Closing date
17 Dec 2023

View more

Discipline
Data Management / Statistics
Hours
Full Time
Contract Type
Permanent
Experience Level
Experienced (non-manager)

Job Details

I am working with a leading Biotechnology company dedicated to advancing healthcare through cutting-edge research and innovation. They are seeking a highly skilled and motivated Data Scientist with excellent technical and software knowledge to join their dynamic team. This position offers the opportunity to contribute to groundbreaking projects that aim to revolutionize our understanding and treatment of immunological disorders.

 

The successful candidate will collaborate with cross-functional teams of scientists, researchers, and analysts to analyse large and complex datasets, develop predictive models, and derive actionable insights to drive the development of novel therapies and diagnostics.

 

Responsibilities:

  • Use cutting-edge statistical and machine learning methods to analyse high-dimensional immunology-related biological data sets.
  • Work together with subject-matter specialists to validate data and understand outcomes in the context of immunology.
  • Apply explainable AI techniques to both new and current models to provide a thorough understanding of their forecasts.
  • Create and put into practice algorithms specific to immunological datasets for feature selection, data preparation, and model optimisation.
  • Closely collaborate with interdisciplinary teams made up of biologists, physicians, and computer scientists to make sure data science initiatives are in line with the objectives of immunological research.
  • Participate in the creation and upkeep of best practices and data standards inside the company.

 

Background:

  • A doctorate or master's degree in bioinformatics, computer science, statistics, data science, or a similar discipline.
  • Expertise in programming languages like R or Python. Proficiency in data visualization, statistical analysis, and machine learning methodologies.
  • Working knowledge of feature engineering, machine learning model development and testing, and exploratory data analysis.
  • Working knowledge of XAI techniques like Layerwise Relevance Propagation, SHAP, LIME, and ELI5.
  • Knowledge of pertinent bioinformatics databases and tools.
  • It is advantageous to have prior experience with deep learning statistical modelling techniques like neural networks, RNNS, CNNS, GANS, etc.
  • Outstanding teamwork and communication abilities.
  • The capacity to operate both alone and in a fast-paced, team-oriented setting.
  • Knowledge in the areas of molecular biology, bioinformatics, and related sciences, or a desire to learn more.

 

Following your application Filipa Englefield, a specialist AI recruiter will discuss the opportunity with you in detail. She will be more than happy to answer any questions relating to the industry and the potential for your career growth. The conversation can also progress further to discussing other opportunities, which are also available right now or will be imminently becoming available. This position has been highly popular, and it is likely that it will close prematurely. We recommend applying as soon as possible to avoid disappointment.

 

Please click ‘apply’ or contact Filipa Englefield for further information.

 

Filipa Englefield

Recruitment consultant – Barrington James

Email: fenglefield@Barringtonjames.com

Company

We’re great at what we do. A collection of the worlds finest Life Science recruiters working for the worlds best Life Science consultancy.

Originally, a purely contingency and contract recruiter, focused in the UK, Barrington James is now a sophisticated, highly effective provider of human resources solutions up to full RPO, partnering the pharma, medical devices, and healthcare industries right across the globe.

Company info
Website
Telephone
01293 776644
Location
Victoria House
Consort Way
Horley
Surrey
RH6 7AF
GB

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