Director, AI Strategy for Biologics at Takeda

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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 Director, AI Strategy where you will lead the strategic application, integration and development of machine learning and AI technologies in the discovery and development of biologics ensuring alignment with Global Biologics and Takeda Research goals to deliver innovative, highly differentiated therapeutic opportunities for patients. You will also drive integration of the modeling pipelines with internal data mining platforms and build a continuous test and learn pipeline. As part of the Global Biologics team, you will report to the Head of the organization and coordinate with internal and external collaborators to build Takeda’s capabilities in this area towards the goal of accelerating drugs to patients.

How you will contribute:

• Lead the integration and advancement of AI technologies in biologics discovery.
• Develop and implement strategic AI initiatives to enhance biologics research and lab processes.
• Oversee AI-driven projects, ensuring alignment with company goals and timely delivery.
• Foster collaboration with internal teams and external partners.
• Build and mentor a high-performing AI and data science team.
• Identify and evaluate academic / industry collaborations and serve as the point of contact with external partners/ stakeholders.
• Proactively assess external opportunities and internalize novel methods and tools.
• Foster a culture of innovation and scientific excellence within the drug discovery team, promoting collaboration, knowledge sharing, and continuous learning.
• Oversee the design and execution of experiments, data analysis, and interpretation to guide decision-making and further learning and optimize drug discovery efforts.
• Stay abreast of the latest advancements in drug discovery, emerging technologies, and industry trends, and apply this knowledge to enhance drug discovery strategies.
• Provide guidance and mentorship to team members, fostering their professional growth and development.
• Communicate and explain strengths and weaknesses of complex computational models and ML techniques to broad scientific audience from diverse disciplines.
• Collaborate effectively within a matrix environment, with scientists across various scientific disciplines, therapeutic areas, and departments to develop a strategy and appropriate goals for data science work.
• Increase the external recognition of Takeda’s data science work by participating in conferences, publishing work and developing external.

Minimum Requirements/Qualifications:

• PhD degree in Computational Biology, Bioinformatics, Computer Science, or a related field with 10+ years experience , or MS with 16+ years experience, or BS with 18+ years experience.
• A minimum of 10 years of experience applying machine learning/ deep learning approaches in the life sciences.
• Proven track record of leading AI-driven projects in a pharmaceutical or biotechnology setting.
• Significant depth of expertise in at least one field relevant to the job (for example, machine learning, biotherapeutic design, etc.).

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.

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Takeda Compensation and Benefits Summary

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:

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-termincentives. U.S.based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S.based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

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.

Locations

Boston, MA

Worker Type

Employee

Worker Sub-Type

Regular

Time Type

Full time