Director – Oncology Genomics, HGG
GSK
Python
Director, Computational Statistics – Human Genetics and Genomics
GSK
full-time
Posted on:
Location Type: Hybrid
Location: Stevenage • 🇬🇧 United Kingdom
Visit company websiteJob Level
Lead
Tech Stack
CloudPython
About the role
- Maintain a clear working understanding of the scientific needs of key partners in applied and translational teams across HGG, in experimental Target Discovery, in GSK disease area Research Units, and in Clinical Development.
- Maintain leading edge understanding of mature and emerging capabilities in computational statistics and in statistical/machine learning, both externally and internally.
- Identify scientific questions within the broad area of human genetics and genomics in drug discovery and development, that will impact GSK portfolio and pipeline decision-making, and formulate these as statistical problems.
- Develop suitable computational methods to address these questions, and implement robust software that scales in a cloud compute environment.
- Make individual scientific and technical contributions, inspire, guide, and develop team members, and plan and assess the (human and computational) resources necessary to achieve this.
- Contribute to a culture of innovation, quality, and continuous learning and improvement within the team.
Requirements
- Advanced degree (PhD or equivalent) in a relevant scientific discipline.
- Substantial research experience (either academic or industry) demonstrating innovative application of statistical approaches to answer scientific questions relevant to drug discovery or development using genomic/genetic data.
- Research experience critically evaluating, improving and testing, and/or developing statistical/machine learning methodology.
- Strong programming skills in R and/or Python.
- Familiarity with techniques in reproducible research, literate programming, FAIR data principles, and agile software development.
- Proficiency in analysis of very large datasets using distributed or cloud computing technologies.
- Familiarity with advantages and limitations of high-performance libraries and tools for large data.
- Strong theoretical understanding of computational statistics, and of statistical and machine learning, with the ability to apply these principles to solve scientific questions that do not easily map to existing solutions.
- Excellent communication, collaboration, influencing and leadership skills.
- Demonstrated delivery of complex and impactful projects, and coordination of multidisciplinary teams.
Benefits
- Competitive salary
- Health insurance
- Flexible working hours
- Professional development opportunities
- Paid time off.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
computational statisticsstatistical learningmachine learningprogramming in Rprogramming in Pythonreproducible researchliterate programmingdata analysiscloud computinghigh-performance libraries
Soft skills
communicationcollaborationinfluencingleadershipinnovationquality improvementcontinuous learningteam developmentproject deliverymultidisciplinary coordination
Certifications
PhD in relevant scientific discipline