Associate Director, Discovery Data Science (New Translational Group)
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Eisai Inc. recently developed new Translational Science department in oncology area, which covers preclinical and clinical translational & biomarker research and clinical pharmacology to accelerate clinical development of candidate oncology drugs. As part of this new department, we are a, Precision Informatics unit. Data science, computational biology and bioinformatics are a fundamentally important core discipline and integral part of Translational Science. This team will play a key role in leveraging internal and external cancer genomics and pharmacogenomics data for developing new breakthrough oncology drugs, with a sharp strategic focus on employing entrepreneurial collaborative and business models to accelerate delivery of innovative medicines that address unmet patient needs.
The Associate Director, Head of precision informatics including Discovery Data Science and bioinformatics, is a member of the Translational Science Engine within the Oncology Business group. This person will be responsible for performing, coordinating, and leading hands-on analysis of exploratory and regulatory related biomarker analysis, large-scale genetic and other ‘omic analyses, with a primary goal of identifying and validating targets and biomarkers in preclinical and clinical trials for oncology. More specifically, this person will design, carry out, and oversee genetic and other ‘omic analyses that will form the foundation of Oncology Business group’s knowledgebase for evaluating and prioritizing drug development. Because Translational Science department places such a strong emphasis on human biology, the Associate Director will evaluate, potentially design, and implement cutting-edge statistical analysis and exploratory informatics methods as needed to do this research. Relevant human biology data will be accessed through internal sources and through current and collaboration partners and may require deep understanding of different classes of human phenotypic data, including EHR/EMR, self-report, and clinical trial data. An ability to strategically evaluate the promise of different data sources and to identify appropriate analytical approaches to using them will be key. This person will also conduct and/or coordinate analysis of other ‘omics data, including WGS/WES/targeted sequencing, epigenetics, RNAseq, microarrays, etc. All analysis work will be documented and will follow best practices for enabling reproducible research.
Principal Duties and Responsibilities:
• Lead the Precision Informatics function with high motivation for the members of this team.
• Develop strategy, implementation plan, and work closely with biomarker team and system and software development team to adopt and develop solutions for biomarker data management, integration and analytics.
• Actively contribute to identification of new technology solutions and CRO options in the domains of biomarker, diagnostics and informatics.
• Conduct data science activities including cleaning, handling, integration, and analysis of small- and medium-scale experimental data generated from cell lines, model organisms, and human subjects, including genotype, mRNA, protein, and other data types.
• Analyze large-scale analysis-ready datasets to answer specific focused questions of relevance to biology project teams.
• Contextualize findings from internal experiments and generate hypotheses for new internal experiments by analyzing and interpreting externally available data.
• Provide appropriate visualization and interpretation of results in preclinical experimental data to support decision making on drug development projects.
• Contribute to preclinical experimental study design to generate statistically meaningful information.
• Prepare and track documentation including analysis plans, result reports, and progress reports.
• MS, Ph.D. degree preferred with 3-5 years of experience in Statistical Genetics, Genetic Epidemiology, Human Genetics, Statistics, or closely related field. Industry experience preferred.
• Must have analytic and statistical skills to conduct analysis of epigenetic, transcriptomic, and proteomic data.
• Must have a good understanding of human biology. Experience in oncology is highly desirable. Must demonstrate good understanding of drug discovery requirements and processes.
• Must have strong organizational skills, ability to prioritize and delegate work and a high level of proficiency in both project and people management.
• Must have excellent communication skills and the ability to act on cross-disciplinary teams;
•Must have experience with R and Unix/Linux systems. Additional experience with languages/software including Spotfire, Bioconductor, Pipeline Pilot, and SQL is preferred. Ability to use Excel and Python may also be useful.