Associate Director, Clinical Data Science

3 weeks ago

Nutley, United States Eisai, Inc. Full time
At Eisai, satisfying unmet medical needs and increasing the benefits healthcare provides to patients, their families, and caregivers is Eisai's human health care (hhc) mission. We're a growing pharmaceutical company that is breaking through in neurology and oncology, with a strong emphasis on research and development. Our history includes the development of many innovative medicines, notably the discovery of the world's most widely-used treatment for Alzheimer's disease. As we continue to expand, we are seeking highly-motivated individuals who want to work in a fast-paced environment and make a difference. If this is your profile, we want to hear from you.

The Clinical Data Science team at Eisai, Inc., is expanding its capabilities by acquiring in-house talent related to bioinformatics, machine learning, and big data analytics for the Oncology and Neurology clinical programs. This position will be focused on the bioinformatics collaborations in Oncology clinical trials and will thus play a crucial role in analyzing large-scale genomic and clinical datasets to uncover insights into cancer biology and treatment response. The successful candidate will work collaboratively with interdisciplinary teams of scientists, clinicians, and bioinformaticians to drive discoveries that have a direct impact on cancer diagnosis, prognosis, and optimal treatment strategies. The qualified candidate will report to the Head of Clinical Data Science and is expected to have the following responsibilities:

• Perform integrative analyses of multi-omics data from clinical trials and research cohorts, including genomics, transcriptomics, proteomics, and imaging, to identify biomarkers related to treatment mechanism and response, and potential therapeutic targets.

• Derive novel prognostic and predictive signatures using statistical and machine learning methods to guide patient stratification and biomarker selection in clinical trials.

• Establish, develop, and implement optimal bioinformatics pipelines for the analysis of next-generation sequencing and other -omics data.

• Collaborate with translational scientists and clinicians to design and execute data analysis strategies that address key clinical oncology research questions.

• Develop and publish relevant bioinformatics methodologies, pipelines, and algorithms, and stay abreast of the latest advancements in bioinformatics, machine learning, and oncology research.

• Present results from complex datasets that are clear and interpretable to both technical and non-technical stakeholders.

Job Qualifications

• Ph.D. in Computational Biology, Biostatistics, or a related field.

• Extensive experience and expertise, demonstrated via a strong publication record and prior work experience, in the analysis of cancer genomics data, including whole-genome sequencing, exome sequencing, RNA-seq, and epigenomic data.

• At least 7 years of experience in the pharma industry or clinical research institution is required.

• Proficient in programming languages such as Python, R, and Perl, with a mastery of various bioinformatics tools and software, along with experience in developing bioinformatics pipelines.

• Demonstrated expertise in statistical theory and a wide range of statistical methods and machine learning techniques for high-dimensional multi-omics data.

• Exceptional communication and collaboration skills, with the proven ability to lead and mentor in a multidisciplinary team environment.

• Previous experience in oncology research is required.

Eisai is an equal opportunity employer and as such, is committed in policy and in practice to recruit, hire, train, and promote in all job qualifications without regard to race, color, religion, gender, age, national origin, citizenship status, marital status, sexual orientation, gender identity, disability or veteran status. Similarly, considering the need for reasonable accommodations, Eisai prohibits discrimination against persons because of disability, including disabled veterans.

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