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Data Scientist - Drug Discovery - OUTSIDE IR35

Hays Specialist Recruitment Limited
Job LocationCambridgeshire
EducationNot Mentioned
Salary265.00 - 340.00 per day
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypeContract , full-time

Job Description

Home based data scientist role leading global pharma company, analysing omics and NGS data using ML, 12 months Your new companyYou will be joining one of the leading global pharmaceutical companies who have an excellent reputation for Research & Development. They have been investing heavily within their Data Science capabilities over the last few years and are continuing to expandtheir teams as well as their technology.Oncology has been a particular focus for them, with multiple new drugs launched over the last few years, and they are looking to add someone to their team who can help drive drug discovery and development efforts through utilising advanced Data Science approachesfor aspects such as personalised medicine and biomarker development.Your new roleThis is a remote / home-based contract position initially lasting 12 months, working closely with a cross-functional team of R&D Scientists, Data Scientists, medics and statisticians to analyse large scale NGS and other omics data sets and support drug discoveryand development efforts by suggesting novel targets and approaches. The role is outside IR35.This position will be focused on oncology research and look at aspects such as immunotherapy, personalised medicine, patient stratification and genetic drivers for cancer. Main responsibilities will include:

  • Hands-on analysis of multi-omic and genetic/genomic data sets
  • Helping develop new ML models and approaches for R&D projects, especially within knowledge graphs / graph-based models
  • Optimise and update knowledge graphs in use for R&D work, eg by incorporating new data sets
  • Help develop new functionality and versions of knowledge graphs
  • Work closely with stakeholders across R&D, eg drug discovery and development team leads to advise on potential drug targets
  • Provide insight and ideas on potential drug discovery strategies and approaches
  • Hands-on programming
What youll need to succeed
  • BSc/MSc/PhD (or equivalent experience) in bioinformatics, computational biology, data science, statistics or a relevant discipline.
  • Track record of working with genomic, NGS or multi-omic data sets (preferably from clinical samples)
  • Knowledge / experience of drug discovery or development, preferably within a pharmaceutical, biotech or CRO
  • Skilled in programming languages such as python or R.
  • Experience using machine learning methods and statistical models.
  • Strong communication skills with the proven ability to relay information effectively and efficiently, both to computational and experimental scientists.
  • Experienced working collaboratively with teams on project work.
Expertise with knowledge graphs or related software (eg Neo4j) would be a significant advantage for this roleWhat youll get in returnAn exciting opportunity to work with one of the leading global players developing novel oncology medicines and having a real impact on future patients around the world.The role is also fully home based (with c.1-2 days per month in the office), offers a good pay rate and is outside IR35.What you need to do nowIf youre interested in this role, click apply now to forward an up-to-date copy of your CV, or call us now.If this job isnt quite right for you but you are looking for a new position, please contact us for a confidential discussion on your career.Keywords: data, science, pharmaceutical, biotech, biology, computational, omic, NGS, genomic, drug, discovery, development, R&D, research, oncology, cancer, knowledge, graph, machine, deep, learning, ML, database, software, neo4j, CRO, project, management,python, programming, pipeline, tool, model, algorithm, statistical

Keyskills :
NGSCROsciencelearningsoftwaredatapythonbiologyR&Dprojectpharmaceuticaldatabasedevelopmentresearchmachineknowledgecancerdrugoncologyneo4jbiotechdiscoverygraphgenomicdeepcomputationalomic

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