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Principal Scientist, Biologics, Computational Biology / Machine Learning

Takeda Pharmaceutical
Marion, New York, US
Closing date
Dec 2, 2021

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Consultancy/Private Sector
Conservation science
Statistics, Biology
Salary Type
Employment Type
Full time
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Job Description

Are you looking for a patient-focused, innovation-driven company that will inspire you and empower you to shine? Join us as a Principal Scientist, Biologics, Computational Biology / Machine Learning in the Global Biologics team at our Cambridge, MA office.

At Takeda, we are transforming the pharmaceutical industry through our R&D-driven market leadership and being a values-led company. To do this, we empower our people to realize their potential through life-changing work. Certified as a Global Top Employer, we offer stimulating careers, encourage innovation, and strive for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our global teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.

Here, you will be a vital contributor to our inspiring, bold mission.


The Global Biologics team at Takeda is focused on creating novel treatments that make a large impact on patients' lives in the fields of Oncology, Gastroenterology, Neuroscience, and Rare Diseases. The Principal Scientist role in Global Biologics will leverage skills in sequence analysis, pattern recognition, machine learning, and scientific programming to develop and implement tools that enable the design of novel therapeutics and prediction of biophysical and therapeutic properties. The scientist will also be responsible for coordinating with internal and external collaborators and interface very closely with members of other therapeutic groups to help build Takeda's capabilities in this area. Responsibilities include:
  • Develop and implement tools and models that enable rapid assessment of biotherapeutics with regard to potency, immunogenicity and developability . Proactively assess and internalize novel methods and tools.
  • Help build and execute on the scientific strategy for building out Takeda's machine learning platform for application in antibody development and gene therapy.
  • Understand and effectively utilize a wide variety of data sources, both proprietary and public, to develop predictions.
  • Independently design studies, ranging from simple to more complex, to test and further refine predictive models.
  • Support all aspects of projects from data wrangling through to machine learning and statistical analysis.
  • Identify potential external collaborations and serve as the point of contact with external partners/ stakeholders.
  • Communicate and explain strengths and weaknesses of complex computational models and ML techniques to broad scientific audience from diverse disciplines.

  • Develop and implement appropriate machine learning/pattern recognition algorithms to help define the design space for engineering biomolecules taking into consideration efficacy, immunogenicity and developability predictions as well as experimental resources.
  • Independently represent Global Biologics function on project and data science teams in support of discovery programs.
  • Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation.
  • Strengthen Takeda's advanced analytics toolkit by identifying and applying emerging techniques, as well as by advancing the state of the art and developing novel analysis tools as needed.
  • 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.
  • Anticipate and communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Propose and implement solutions. Escalate issues to management as appropriate in a timely manner.
  • Increase the external recognition of Takeda's data science work by participating in conferences, publishing work and developing external collaborations.

  • Track record of applying machine learning/ deep learning approaches, to solve drug discovery and development problems.
  • Education in a relevant field, for example a) PhD in a field such as Biostatistics, Physics, Computation Biology, Biomedical Engineering, Computer Science, Applied Mathematics with at least 6 years of experience and a clear interest in data science methods, or b) Master's degree with at least 9 years of relevant experience.
  • Expert-level knowledge of data science programming languages (Python and R, or similar).
  • Significant depth of expertise in at least one field relevant to the job (for example, machine learning, biotherapeutic design, etc.).
  • Track record of applying machine learning/ deep learning approaches, to solve relevant biological problems.
  • Familiarity with concepts, techniques, and common tools used for sequence analysis, pattern recognition and protein structure modeling.
  • Ability to work independently on complicated datasets, including all aspects of data analysis (data cleaning, algorithm development, statistical analysis, and documentation).
  • Excellent oral and written communications skills.
  • Strong project management skills.
  • Willingness and ability to self-educate in new areas.
  • Strong collaborative skills and ability to work with a cross-functional team.

  • 401(k) with company match and Annual Retirement Contribution Plan
  • Tuition reimbursement Company match of charitable contributions
  • Health & Wellness programs including onsite flu shots and health screenings
  • Generous time off for vacation and the option to purchase additional vacation days
  • Community Outreach Programs

Empowering Our People to Shine

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This job posting excludes CO applicants.


EEO Verbiage for US Reqs

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.


Boston, MA

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