Manager, Nonclinical Statistics

Role Summary

Manager of Nonclinical Statistics in Cambridge, MA. Provide statistical leadership across nonclinical functions, applying experimental design, advanced statistical tools, and decision theory to improve patient access to modern medicines. Support preclinical and clinical biomarker assay development and validation, and collaborate across CMC and drug discovery spaces.

Responsibilities

• Provide statistical support and leadership for CMC campaigns for design and analysis in analytical development and formulation development for synthetic molecules, biologics, cell therapies, and other drug modalities.
• Provide statistical support and leadership for preclinical and clinical biomarker assay development and validation.
• Collaborate with Global Manufacturing, Regulatory Affairs, and Global Quality to explore methods and implement CMC strategies to enable data driven decision making.
• Apply frequentist, Bayesian, ML/AI fit-for-purpose statistical analyses across various projects and data types in the preclinical R&D arena.
• Contribute to and/or serve as lead representing data science on project teams in support of nonclinical studies across analytical development, formulations development, and other CMC functions.
• Develop and validate preclinical and clinical biomarker assays for all therapeutic areas.
• Perform end-to-end data analyses from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analyses, to planning reports and documentation.
• Strengthen analytics toolkit by identifying emerging techniques and developing novel analysis tools as needed.
• Collaborate within a matrix environment with scientists across areas to tailor data analyses to program-specific needs.
• Work closely with Takeda statisticians to address statistical issues in data analysis.
• Communicate resource and quality issues that may impact deliverables or timelines; escalate as appropriate.
• Respond to regulatory questions that are statistical in nature.
• Increase external recognition of Takeda’s data science work by participating in conferences, publishing work, and developing external collaborations.

Qualifications

• Education in a relevant field, for example a PhD in Statistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics with relevant experience, or a Master’s degree with a minimum of 3 years of relevant experience.
• Hands-on experience with and strong interest in CMC and/or assay development and validation.
• Expert-level knowledge of data science programming languages (R, Python, or similar) and experience with software development practices.
• Ability to work independently on complex datasets, including data cleaning, algorithm development, statistical analysis, and documentation.
• Excellent oral and written communications skills.
• Willingness and ability to self-educate in new areas.
• Knowledge of FDA, EMA, and ICH regulations and industry standards applicable to CMC is a plus.

Skills

• Statistical leadership in nonclinical settings
• Experimental design and data analysis (frequentist and Bayesian approaches)
• Machine learning / AI tools applied to biomedical data
• Biomarker assay development and validation
• Cross-functional collaboration in a matrix organization
• Strong communication of complex statistical concepts to non-statisticians

Education

• PhD in Statistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics with relevant experience, or Master’s degree with at least 3 years of relevant experience