Manager, Statistics

Takeda•Boston, MA

9d•Hybrid

About The Position

Takeda Development Center Americas, Inc. is seeking a Manager, Statistics to represent the data science function on global teams supporting pre-clinical and clinical studies and compound-level programs. The role provides leadership in developing and reviewing study synopses, protocols, statistical analysis plans, and clinical study reports, ensuring deliverables are accurate and statistically valid. The Manager performs end-to-end data analyses, from formulating hypotheses and designing experiments through writing analysis plans, cleaning and analyzing data, and preparing reports and documentation. The role supports reproducible, interpretable research and strong data-handling and data-provenance practices. It also strengthens Takeda’s advanced analytics toolkit by applying emerging techniques, advancing methods, and developing analysis tools as needed. Working in a matrix environment, the Manager collaborates with scientists across therapeutic areas and colleagues in pharmacology, chemistry, imaging, translational sciences, computational biology, and experimental medicine. The role works closely with Takeda statisticians, anticipates and communicates resource or quality issues that could affect deliverables or timelines, proposes solutions, and escalates issues when appropriate. The position also builds the impact and recognition of Takeda’s data science work through cross-therapeutic-area opportunities, conference participation, publications, and external collaborations. Up to 75% remote work is allowed, with five onsite workdays required per month.

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 reviews, mathematical derivations of statistical methodology, real-world data applications, and preparation of written reports or publications.
Experience implementing reproducible statistical workflows for high-dimensional data analysis and methodological evaluation using R, Python, and SAS, and UNIX operating systems in High-Performance Computing environments.
Experience applying statistical methods and deep learning approaches, including survival analysis, longitudinal data analysis, and deep neural network models, to evaluate hypotheses and interpret results in biomedical and clinical data for cross-functional research teams.

Responsibilities

Represent the data science function on global project teams supporting pre-clinical and clinical studies and compound-level programs.
Lead 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, including hypothesis formulation, experimental design, analysis planning, data cleaning, analysis execution, and preparation of reports and documentation.
Develop and support best practices for data handling and data provenance 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 define or develop appropriate data science goals, including identifying or developing endpoints for patient-population segmentation, disease-progression tracking, 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 resource and quality issues that may affect program deliverables or timelines; propose and implement solutions and escalate issues to management as appropriate.
Identify data science opportunities across therapeutic areas to increase the internal impact of Takeda’s work.
Participate in conferences, publish work, and develop external collaborations to increase external recognition of Takeda’s data science work.