Director, Computational Biology

Objective / Purpose

The Director, Oncology Computational Biology will be a key scientific leader within the Computational Biology and Human Genetics (CBHG) team. This individual will serve as a hands‑on expert in cancer genetics/genomics and computational approaches to oncology, driving the discovery and prioritization of novel oncology targets and therapeutic concepts across Takeda’s Oncology portfolio.

• Serve as a scientific leader in cancer genetics/genomics and computational oncology, driving AI/ML‑enabled target identification, prioritization, and validation strategies to advance a differentiated oncology discovery portfolio.
• Lead the application of advanced computational approaches to oncology target discovery and validation, integrating multimodal datasets to uncover novel biological mechanisms, therapeutic opportunities, biomarkers, and patient stratification hypotheses.
• Develop and apply rigorous computational frameworks that integrate genomic, transcriptomic, functional dependency, clinical, proteomic, and other high‑dimensional datasets to generate actionable insights supporting oncology target identification and validation.
• Establish scalable AI/ML‑driven ways of working for oncology target discovery, enabling systematic hypothesis generation, target evaluation, and evidence integration across diverse internal and external data sources.
• Partner closely with oncology biology, target validation, translational, and drug discovery teams to ensure computational insights are biologically grounded, experimentally testable, and directly aligned with target validation and portfolio progression activities.
• Collaborate with AI/ML, data science, and data engineering teams to build scalable analytical capabilities, reusable workflows, and high‑quality oncology data assets that accelerate target discovery and validation across the Oncology Research organization.
• Help shape Takeda’s oncology computational and data strategy, identifying opportunities to enhance target discovery and validation capabilities through external collaborations, strategic partnerships, emerging AI technologies, and novel data resources.
• Influence scientific and portfolio decisions through clear communication of complex computational, biological, and translational findings to cross‑functional teams and senior leadership.
• Lead and contribute to complex, multidisciplinary oncology discovery programs in a highly collaborative matrix environment, serving as a key computational driver of oncology target /validation efforts.

• PhD in Computational Biology or a related discipline, plus 10+ years of track record of scientific innovation and impact.
• Recognized expert in cancer genetics/genomics and oncology computational biology.
• Expertise in machine learning and complex algorithms required, with experience in AI/LLMs/biological foundation models strongly preferred.
• Industry experience supporting oncology target .
• Demonstrated ability to lead complex projects in a matrix environment.
• Strong organizational skills; ability to set priorities and meet program objectives and timelines.
• Strong written and oral communication skills to diverse audiences.

• The position will be based in Cambridge, MA. This position is currently classified as “hybrid” by Takeda’s Hybrid and Remote Work policy.

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For

Location:

Boston, MA

U.S. Base Salary Range: $ - $

The estimated salary range reflects an anticipated range for this position. The actual base salary offered may depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.

The actual base salary offered will be…