Director, Computational Biology

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Job Description

Objective /

Purpose:

The Director, Oncology Computational Biology will be a key member of the Computational Biology and Human Genetics (CBHG) team, within the Computational Science and Data Strategy department. The Director will be a hands-on expert in cancer genetics/genomics and computational oncology, and will drive oncology Target  validation, drug discovery, and indication selection in a cross-functional environment comprised of cancer biologists, drug discovery experts, translational scientists, AI/ML experts, and many others.

The Director will be responsible for establishing rigorous frameworks for high-dimensional data analysis, executing analyses to generate insights across the Oncology Research portfolio, and shaping the oncology data and analytics environment to be broadly deployed to Takeda’s Oncology Research community.

Accountabilities:

• As a recognized expert in cancer genetics and
  -omics, and in computational methods for harnessing high-dimensional oncology-relevant data, set strategy and generate rigorous insights impacting all stages of the Oncology Research (Drug Discovery Unit) portfolio

• Design and implement computational approaches to systematically identify, evaluate, and prioritize new cancer drug targets and their potential indications

• Design and implement computational biology approaches to evaluate the suitability of targeting approaches and of therapeutic leads

• Drive the development of Takeda’s oncology data ecosystem. Identify gaps and opportunities to fill them, including by external collaboration, as needed.

• Work closely with data science and engineering colleagues to deploy data and analytical techniques to the Oncology Research community, to democratize the rigorous generation of insights

• Work closely with AI/ML teams to define and implement cutting-edge AI models, including LLMs and biological foundation models, which help generate novel insights rooted in well-curated data and rigorous statistical approaches

• Manage resources and priorities in complex, multi-disciplinary teams

• Communicate complex results to diverse audiences, including bench scientists, portfolio managers, and senior leadership

Education & Competencies

• PhD in Computational Biology or a related discipline, plus 10+ years of experience

• 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 preferred

• Industry experience supporting target /or drug discovery preferred

• 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

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 in accordance with state or local minimum wage requirements for the job location.

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company…