Director, Computational Statistics, Human Genetics and Genomics

Role Summary

Director, Computational Statistics, Human Genetics and Genomics at GSK. Lead key activities to progress genomic technologies and apply computational statistics and machine learning to understand gene-phenotype links and guide drug discovery and development.

Responsibilities

• Maintain a clear working understanding of the scientific needs of key partners across HGG, experimental Target Discovery, disease area Research Units, and Clinical Development.
• Maintain leading edge understanding of mature and emerging capabilities in computational statistics and statistical/machine learning, collaborating with Biostatistics, Data Automation and Predictive Sciences, and AIML departments.
• Identify scientific questions within human genetics and genomics relevant to drug discovery and development, and formulate these as statistical problems.
• Develop computational methods to address these questions and implement robust software that scales in a cloud compute environment. Lead, guide and develop team members and plan resources.
• Contribute to a culture of innovation, quality, and continuous learning and improvement within the team.

Qualifications

• Advanced degree (PhD or equivalent) in a relevant scientific discipline.
• Substantial research experience applying statistical approaches to genomic/genetic data for drug discovery or development; evaluating, improving, testing, or developing statistical/machine learning methodology.
• Strong programming skills in R and/or Python; familiarity with reproducible research, FAIR data principles, agile software development; ability to analyze very large datasets using distributed or cloud computing; familiarity with high-performance libraries for large data.
• Strong theoretical understanding of computational statistics and machine learning; ability to apply principles to complex questions.
• Excellent communication, collaboration, influencing, and leadership skills; track record of delivering complex, impactful projects and coordinating multidisciplinary teams.

Skills

• Computational statistics
• Statistical/machine learning
• Genomics/genetics data analysis
• Cloud computing and scalable software development
• Programming in R and Python
• Cross-functional collaboration and leadership