
Senior Manager of Statistics- CMC
- Cambridge, MA
- Permanent
- Full-time
- Provide statistical support and leadership for Takeda 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 Takeda clinical and 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.
- Contribute to and/or serve as lead representing data science function on project teams in support of nonclinical studies throughout analytical development, formulations development, and other CMC functions.
- Develop and validation clinical and biomarker assays for all therapeutic areas.
- 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 developing novel analysis tools as needed.
- Collaborate effectively within a matrix environment, working with scientists across various areas to understand the problems in terms of its chemistry, biology, and/or physical natures and to tailor data analyses to program-specific needs.
- Work closely with Takeda statisticians to ensure statistical issues in data analysis are addressed.
- Communicate internal and external resource and quality issues that may impact deliverables or timelines of the program. Escalate issues to management as appropriate in a timely manner.
- Respond to regulatory questions that are statistical in nature.
- Increase the external recognition of Takeda’s data science work by participating in conferences, publishing work and developing external collaborations.
- Education in a relevant field, for example a) PhD in a field such as (Bio)statistics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics with at least an additional 3 years of experience in a statistical or quantitative field, or b) Master’s degree with a minimum of 6 years of relevant experience
- Hands on experience with and strong interest in some of the relevant fields of CMC and/or assay development and validation.
- Expert-level knowledge of data science programming languages (R, Python, or similar) and experience with recommended practices for software development.
- 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.
- Willingness and ability to self-educate in new areas.
- Knowledge of FDA, EMA, and ICH regulations and industry standards applicable to the CMC is a plus.