Statistical Bioinformatician - UK

GSK's goal is to be one of the world's most innovative, best performing and trusted healthcare companies. We have 3 global businesses that research, develop and manufacture innovative pharmaceutical medicines, vaccines and consumer healthcare products. We are committed to widening access to our products, so more people can benefit, no matter where they live in the world or what they can afford to pay. GSK has a thriving global community of statisticians across the three divisions of our company. Within the pharmaceutical division, our clinical statisticians are industry leading experts in data analysis and methodologic research. Our end-to-end project support model ensures that our statisticians collaborate across the entire range of drug development, from early clinical development, to registration and marketed product support. Details The successful candidate will serve as an expert computational scientist in the Statistical Bioinformatics team and will have the opportunity to contribute significantly to the clinical biomarker objectives and influence the translational medicine efforts and companion diagnostic development. Key Responsibilities include, but are not limited to: * Provide high quality and timely support for the various biomarker projects across all phases of drug development pipeline in collaboration with other functional area scientists. * Embrace and consider a wide range of classical and modern data analytic and predictive modeling (machine learning) methods and solutions. * Propose and implement optimal and fit-for-purpose statistical and computational solutions for various biomarker studies. * Proactively give and receive feedback on the projects supported by all members of the Statistical Bioinformatics team to ensure high quality contributions for biomarker needs in the drug development pipeline. * Develop and automate data analysis and visualization tools. * Maintain proficiency in applying a variety of classical and modern statistical methods and machine learning algorithms and be competent in explaining and justifying the methods used. * Lead the development and evaluation of new statistical methods and machine learning algorithms for research topics of greatest need. * Significantly contribute to the external scientific community via conference presentations, publications and collaborations. * Stay current with ongoing external research and literature on statistical and predictive modeling (machine learning) methods for biomarker applications and be competent in explaining and justifying the methods used. * Help develop new statistical methods and machine learning algorithms for precision medicine and related drug development needs. * Contribute to the external scientific community via conference presentations, publications and collaborations. The ideal candidate will possess: * Strong potential to work with a wide variety of biomarker data such as genomics, proteomics and imaging from various traditional and cutting-edge analytical platforms and expertise in applying sound computational and statistical approaches for processing and analyzing data from these platforms. * Keen interest in learning the scientific and technological elements of the projects. * Ability to proactively learn and contribute to the scientific discussions beyond the core statistical elements. * Demonstrated expertise in applying sound computational and statistical approaches for processing and analyzing data from these platforms. * Demonstrated ability to proactively contribute to the project strategy and decisions beyond the core data analysis elements. * An analytical and inquisitive mind with a proven track record for problem solving. * Well-honed written and oral communication skills. * A proven ability to build effective and trusting relationships with members of interdisciplinary matrix teams. * A proven ability to build powerful networks within and outside the company and use these relationships to achieve support for the planning and implementation of innovative approaches. Why You? Basic Qualifications: * PhD in statistics, computational sciences or related field with focus on methods for genomics and related high-dimensional data analysis, preferably some relevant pharmaceutical research experience with high-dimensional biomarker data from clinical trials, or Masters in statistics or related field with relevant experience and demonstrated potential of applying advanced statistical methods. * Strong statistical foundation with a wide breadth of interest and expertise in classical and modern statistical and machine learning methods. * Ability to apply innovative and fit-for-purpose statistical and predictive modeling methods for the analysis of biomarker and high dimensional data from clinical trials. * Strong programming skills in R with demonstrated potential to develop and automate analysis scripts and tools for broader use. * Excellent interpersonal and communication skills, with strong potentia