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Sr. Scientist, Neuroscience Computational Biology

Takeda
United Statesfull_timeVerifiedPosted 21 Jan 2026
💰 $215,270/yr($137,000/yr$215,270/yr)

About the role

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Job Description

Objective / Purpose:

Join Takeda as a Senior Scientist, Computational Biology, and become part of a global team that leverages cutting-edge computational biology and AI/ML techniques to rigorously identify and evaluate disease-target-biomarker relationships, and derives novel insights for drug discovery, indication expansion, and biomarker development. As a Senior Scientist within the Neuroscience computational group, you will be a part of the Computational Sciences department and will engage with key stakeholders across diverse Takeda  R&D teams (e.g., discovery biology, translational medicine, biomarker sciences, clinical development, and AI/ML), as well as with CROs and academic partners. You will apply expertise in bioinformatics, genomics, machine learning, and computational biology to integrate and analyze pre-clinical and clinical, internal and public multi-omics datasets, to accelerate Takeda’s Neuroscience pipeline and bring transformative medicines to patients.

Accountabilities:

                                                                                                                                                                                                   

  • Serve as a subject matter expert in projects requiring multiomic and high-dimensional data analyses within Neuroscience portfolio at late preclinical and clinical stages including neurodegenerative, neuromuscular and sleep disorders.
  • Apply state-of-the art bioinformatics, AI/ML and computational approaches to analyze multi-omics data from preclinical and clinical studies to identify novel drug targets, and to identify and validate biomarkers for patient selection and indication expansion.
  • Apply large language models (LLMs), disease- and molecular-level knowledge graphs, and foundation models to integrate diverse data types and drive insight generation.
  • Design and apply computational and machine learning methods to analyze, integrate, visualize, and interpret single-cell and spatial transcriptomics, proteomics (e.g., Olink, SomaScan, NULISA, and LC/MS), and metabolomics.
  • Integrate and harmonize large-scale human disease data, including pre-clinical and clinical, internal and public 'omics datasets such as UK Biobank, AMP-AD/PD/ALS, and MESA.
  • Present scientific reports in internal meetings in all settings and with participants of all levels of the organization, as well as for external audiences.
  • Establish partnerships and maintain a collaborative, integrated role with teams to influence the experimental design, assays, data generation, analysis, integration, and interpretation.
  • Proactively identify complex obstacles, recommend and implement solutions using a diverse set of resources.
  • Work collaboratively with data and quantitative scientists and data engineers to enhance our computational infrastructure and data visualization tools


 

Education & Experience

  • PhD degree in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience Prior industry experience with strong background in applying computational biology to research, translational, and/or clinical programs, with a demonstrated ability to meet program objectives and timelines.

Technical Competencies

  • Demonstrated experience in large-scale multi-omics and multimodal data integration, network analysis, and meta-analysis.
  • Experience applying AI/ML methods to biological or biomedical data
  • Statistical analysis experience, including working knowledge of cross-sectional and longitudinal modeling and multivariate data analysis
  • Experience in computational method evaluation, development, and implementation.
  • Fluency in at least one programming language (e.g., Python or R), with demonstrated experience using libraries for statistical, bioinformatic, and AI/ML analyses.
  • Familiarity with high-performance computing (HPC), relational databases (e.g., SQL), and cloud computing platforms (e.g., Amazon Web Services), along with solid knowledge of Unix/Linux environments.
  • Strong organizational, collaboration, and commun

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Company

Takeda

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