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Senior Scientist, Computational Biology, GI DDU

Takeda Pharmaceutical
Santee, California, US
Closing date
Sep 29, 2022

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Academic / Research
Informatics / GIS
Modeling, Biology
Salary Type
Employment Type
Full time
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Job Description

About the role:

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on four therapeutic areas and other targeted investments, we push the boundaries of what is possible in order to bring life-changing therapies to patients worldwide.

Join Takeda as a Senior Scientist where you will to join a multi-disciplinary group that finds novel drug targets, elucidates molecular and cellular mechanisms of action and evaluates efficacy of new drug candidates to treat Gastrointestinal and liver diseases such as:

Celiac Disease
GI motility Disorders
Liver Fibrosis

You will apply state-of-the art bioinformatics and computational approaches to generate and analyze multi-omic data to identify potential biomarkers for patient stratification and explore mechanisms of response or resistance to treatments in GI disorders, and play an important role in our mission to provide innovative therapies for gastrointestinal diseases.

As part of the Gastroenterology Drug Discovery Unit (GI DDU) team, you will report to the Senior Scientist, Gastroenterology Computational Biology and engage with key stakeholders (including clinical development team, translational medicine biomarker team, GI DDU biologists,) to define and execute biomarker data analysis plan, contributing to multiple pre-clinical and clinical stage projects, being the senior scientific consultant or as manager of a smaller, early stage matrix project team.

How you will contribute:

Use high dimensional datasets including multi-omics datasets, from preclinical and clinical studies to identify and execute biomarker studies, patient stratification, and novel drug targets.
Perform systems and multi-modal data integration to summarize data-driven or hypothesis-driven analyses to support mechanism of action, identification of molecular predictors, and achieve translational medicine goals.
Prepare and present comprehensive technical reports and scientific reports for internal meetings in all settings and with participants of all levels of the organization, and for external audiences.
Establish partnership with and maintain a collaborative, integrated role with project teams to influence the experimental design, assays needed, data generation, analysis, integration and interpretation. Participate in due diligences of external opportunities when needed.
Independently design, develop, and execute research assignments in collaboration with GI DDU biologists, contributing to multiple projects.

Minimum Requirements/Qualifications:

PhD degree in Systems Biology, Bioinformatics or Computational Biology with 3+ years post-doctoral experience, or MS with 9+ years experience, or BS with 11+ years experience.
Scientific understanding of computational biology, omics analysis and machine learning-driven biomarker discovery.
Experience in computational method implementation and algorithm generation with the ability to evaluate/develop computational methods based on project needs.
Background in multi-omics driven biomarker analysis.
Develop in-silico data strategy and creative methods for integration of multi-omic and genome wide data.
Experience with single cell and spatial transcriptomics or spatial high content imaging data.
Demonstrated experience with large-scale omics and high-throughput data analysis, network analysis, and meta-analyses.
Working knowledge of drug discovery and development including experience in a matrix team environment is required.
Solid knowledge of Unix/Linux, command line interfaces, and fluency in some common scripting and/or programming language (R, python, etc) used for statistical and computational multi-omics analysis.
Proficiency with classification and machine learning methods.
Statistical analysis experience working knowledge of regression analysis, multivariate data analysis, and linear/nonlinear mixed effects modeling.

What Takeda can offer you:

Comprehensive Healthcare: Medical, Dental, and Vision
Financial Planning & Stability: 401(k) with company match and Annual Retirement Contribution Plan
Health & Wellness programs including onsite flu shots and health screenings
Generous time off for vacation and the option to purchase additional vacation days
Community Outreach Programs and company match of charitable contributions
Family Planning Support
Flexible Work Paths
Tuition reimbursement

More about us:

At Takeda, we are transforming patient care through the development of novel specialty pharmaceuticals and best in class patient support programs. Takeda is a patient-focused company that will inspire and empower you to grow through life-changing work.

Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.

This position is currently classified as "hybrid" in accordance with Takeda's Hybrid and Remote Work policy.

In accordance with the CO Equal Pay Act, Colorado Applicants Are Not Permitted to Apply.


EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.


San Diego, CAWorker Type

EmployeeWorker Sub-Type

RegularTime Type

Full time

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