Scientific Leader, Statistical Bioinformatics
- Collegeville, PA
Site Name: USA - Pennsylvania - Upper Providence
Posted Date: Jun 28 2020
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.
The successful candidate will serve as an expert scientific leader in the Statistical Bioinformatics team and will have the opportunity to be closely engaged in the clinical biomarker objectives and significantly 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.
The ideal candidate will possess:
- Experience with a wide variety of biomarker data such as genomics, proteomics and imaging from various traditional and cutting-edge analytical platforms.
- 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.
- PhD in statistics, computational methods or related field with focus on methods for genomics and related high-dimensional data analysis.
- At least 5 years of relevant pharmaceutical research experience with high-dimensional biomarker data from all phases of clinical trials, or Masters in statistics or related field with at least 10 years of relevant experience.
- Highly proficient in a wide range of classical and modern statistical and machine learning methods, with good external reputation via strong publications and conference presentations.
- Strong multi-tasking and self-management skills.
- Demonstrated ability to lead the computational support for multiple clinical studies/projects.
- Develop and execute sound analysis strategy in a timely manner with clear and insightful presentation and reporting skills.
- Demonstrated 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 ability to develop and automate analysis scripts and tools for broader use.
- Excellent interpersonal and communication skills, with a proven track record of building and maintaining strong working relationships.
- A demonstrated ability to explain novel and standard methods to scientific and clinical colleagues.
- Background in biological sciences, bioinformatics and computational biology.
- Strong track record of methodological and applied research, conference presentations and publications.
- Experience in applying Bayesian statistical methods in biomarker applications.
- Prior experience in precision medicine and drug development.
- Programming experience in other languages such as Python, Perl, SAS, etc.
- Experience providing statistical support for the development of companion diagnostics
If you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US).
GSK is an Equal Opportunity Employer and, in the US, we adhere to Affirmative Action principles. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.
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