Sr. Scientist, NS Computational Biology

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Job Description

Objective / Purpose: Describe at the highest level the team where this job sits and how this role will contribute to the team’s delivery of critical function.

Join Takeda as a Senior Scientist, Computational biologist, 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 utilize human genetics to derive novel insights for drug discovery, indication expansion, and biomarker development. As part of the Computational Sciences team, you will be a senior scientist within a Neuroscience computational group and will report to the NS Computational Biology Group leader. You will engage with key stakeholders including computational science and R&D teams (e.g., discovery biology, pre-clinical sciences, translational medicine and biomarker teams, clinical teams, quantitative sciences, therapeutic area units and engineering) as well as be an integral collaborator with internal cross-functional groups, CROs, and academic partners. The goal of this role is to apply expertise in bioinformatics, genomics, machine learning, and computational biology to integrate and analyze pre-clinical and clinical, internal and public ‘omics datasets focusing on biomarker development, indication expansion, patient stratification, target validation, and target identification.

Accountabilities: Describe the primary duties and responsibilities of the job. Include only the essential functions of the job. Approximately 5 – 10 bulleted task statements should be identified.

• Serve as a subject matter expert in projects requiring genomic and high-dimensional data analyses within Neuroscience portfolio at preclinical and clinical stages including neurodegenerative and neuromuscular diseases.  
• Apply state-of-the art bioinformatics and computational approaches to analyze multi-omics data from preclinical and clinical studies to identify novel drug targets and biomarkers, stratify patients and elucidate molecular, cellular mechanisms of action, support indication expansion.
• Perform multi-omics and multi-modal data integration to identify molecular predictors, inform pathway/target mechanism of action, and achieve translational medicine goals.
• Support target identificaiton and validation for selected neurological disorders.
• Design and apply computational methods to analyze, integrate, visualize, and interpret bulk and single cell readouts (scRNA-Seq, snRNA-Seq), proteomics (Olink, SomaScan, LC/MS), metabolomics, and spatial transcriptomics.
• Integrate and harmonize large-scale human disease data, including pre-clinical and clinical, internal and public 'omics datasets.
• To be familiar with large scale human omics datasets such as AMP-AD, AMP-PD, UKB.
• 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 engineering groups to enhance our computational infrastructure, build on innovative C&SB solutions and intuitive mu