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Principal Computational Genetics Scientist

2 months ago

Slough, Slough, United Kingdom Lifelancer Full time
Job Summary

We are seeking a highly skilled Principal Computational Genetics Scientist to join our global biopharma client on a contract basis for an initial 12-month period. The role will involve a hybrid work arrangement, with 2 days spent in the office and 3 days working from home.

This is an excellent opportunity for a talented individual to make a significant impact on our research and development pipeline. The successful candidate will be part of a dynamic and innovative team that develops and applies cutting-edge analytics and approaches to address complex questions.

Key Responsibilities
  • Support the analytical workload within the genetics group, utilizing expertise in statistical genetics and computational skills to drive project success.
  • Contribute to and potentially lead projects with an outward-facing role, collaborating with cross-functional teams to deliver high-quality results.
  • Develop and apply advanced analytics and approaches to analyze genetic data generated through multiple platforms, providing actionable insights to inform business decisions.
Requirements
  • Direct experience in analyzing and utilizing genetic data, with a strong background in statistical genetics and computational skills.
  • Expert knowledge of statistics, with a focus on statistical genetics and experience in applying machine learning or artificial intelligence approaches.
  • Advanced computational skills, including proficiency in R, Python, SQL, and bash, with experience working in a cloud environment.
  • Ability to interpret and present complex data in a clear and concise manner, with excellent communication and problem-solving skills.
Preferred Qualifications
  • Experience in applying genetics and genetic approaches to drug discovery and development, with a strong understanding of the drug discovery process.
  • Expertise in methods for functional interpretation of genomics data, including variant and gene pathway mapping and enrichment.
  • Ability to understand and integrate data from other sources, such as transcriptomics and proteomics.
  • Relevant biology expertise and experience in working with population databases.
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