Manager, Statistics

Takeda•Boston, MA

10d•$116,000 - $182,270•Hybrid

About The Position

Takeda Development Center Americas, Inc. is seeking a Manager, Statistics to represent the data science function on global project teams supporting pre-clinical and clinical studies and compound-level programs. The role leads the development and review of study synopses, protocols, statistical analysis plans, and clinical study reports, ensuring accurate and statistically valid deliverables. The Manager performs end-to-end data analyses, including hypothesis formulation, experimental design, analysis planning, data cleaning, analysis execution, and preparation of reports and documentation. The role develops data-handling and provenance practices using reproducible, interpretable research approaches and strengthens Takeda’s advanced analytics capabilities by applying emerging techniques and developing novel analysis tools as needed. Working in a matrix environment, the Manager collaborates with scientists across therapeutic areas and with colleagues in pharmacology, chemistry, imaging, translational sciences, computational biology, and experimental medicine. The role works closely with Takeda statisticians on statistical issues, anticipates and communicates resource or quality issues that could affect program deliverables or timelines, proposes and implements solutions, and escalates issues to management when appropriate. The position also identifies opportunities to increase the internal impact of Takeda’s data science work and contributes to its external recognition through conferences, publications, and external collaborations. The position is based in Cambridge, Massachusetts, with up to 75% remote work allowed and five days of onsite work required per month. The posting also lists Boston, Massachusetts as a location.

Requirements

Ph.D. in Statistics or a related field.
Experience developing Bayesian hierarchical models incorporating stick-breaking processes and weights for prediction and inference.
Experience designing and conducting simulation studies to evaluate statistical methods, including defining assumptions, generating data, and summarizing results.
Experience conducting independent statistical research projects, including literature review, mathematical derivations of statistical methodology, real-world data application, and preparation of written reports or publications.
Experience implementing reproducible statistical workflows for high-dimensional data analysis and methodological evaluation using R, Python, SAS, and UNIX operating systems, including High-Performance Computing.
Experience applying statistical methods and deep learning approaches, including survival analysis, longitudinal data analysis, and deep neural network models, to evaluate hypotheses and interpret biomedical and clinical data for cross-functional research teams.

Responsibilities

Represent the data science function independently on global project teams supporting pre-clinical and clinical studies and compound-level programs.
Lead the development and review of study synopses, protocols, statistical analysis plans, and clinical study reports, ensuring accurate and statistically valid deliverables.
Perform end-to-end data analyses, from hypothesis formulation and experimental design through analysis planning, data cleaning, analysis execution, and preparation of reports and documentation.
Develop and support data-handling and data-provenance practices using reproducible, interpretable research approaches.
Identify and apply emerging analytical techniques, advance the state of the art, and develop novel analysis tools as needed.
Collaborate with scientists across therapeutic areas to understand disease biology and identify or develop appropriate data science goals, including endpoints for patient segmentation, disease progression, and quality-of-life measurement.
Collaborate with colleagues in pharmacology, chemistry, imaging, translational sciences, computational biology, and experimental medicine.
Work with Takeda statisticians to address statistical issues in data analysis.
Anticipate and communicate internal and external resource or quality issues that could affect program deliverables or timelines; propose and implement solutions and escalate issues to management as appropriate.
Identify opportunities across therapeutic areas to increase the internal impact of Takeda’s data science work.
Participate in conferences, publish work, and develop external collaborations to increase external recognition of Takeda’s data science work.