Takeda is looking to solve the problem of providing data science expertise to support the design, analysis, and interpretation of preclinical studies, and to enable quantitative decision making from target identification through lead optimization.
Requirements
- Expert-level knowledge of data science programming languages (R, Python, and/or SAS) and experience with recommended practices for software development
- Advanced knowledge of pharmaceutical industry, overall drug development process with expertise in the cross-functional interfaces with the Statistics function
- Significant depth of expertise in at least one field relevant to the job (for example, machine learning, signal processing, etc.) and strong background in both supervised and unsupervised machine learning
- A working knowledge of UNIX operating systems is preferred, ideally with experience in high-performance computing environments
- Hands on experience with and strong interest in some of the relevant fields of biology, and experience supporting programs in Neuroscience, GI, Immunology, Oncology
- Ability to work independently on complicated datasets, including all aspects of data analysis (data cleaning, algorithm development, statistical analysis, and documentation)
- Strong collaborative skills and ability to work with a cross-functional team
Responsibilities
- Providing statistical support in the design, analysis, and interpretation of preclinical studies to enable quantitative decision making from target identification through lead optimization
- Contributing statistical modeling expertise to cross-functional project teams, working closely with colleagues from Discovery biology, translational research, and partner lines
- Effectively working with and gleaning insights from a wide variety of data sources, from standard in-vitro & in-vivo assays to complex imaging data or sensor data
- Applying state-of-the-art data science methodologies (taken from statistics, machine learning, and AI) and fit-for-purpose statistical analysis in support of Discovery efforts from projects start through all stages towards IND
- Serve as global statistical lead for preclinical statistics across therapeutic areas
- Play a leadership role in development and completion of major data analysis deliverables and milestones in collaboration with other functions
- Perform end-to-end data analyses, from hypotheses formulation, experimental design, writing analysis plans, data cleaning, executing analysis, and preparing reports and documentation
Other
- Education in a relevant field, for example a) PhD in a field such as Biostatistics, Applied Mathematics, Physics, Electrical Engineering, Biomedical Engineering, Computer Science with at least 6 years of experience, or b) Master’s degree with a minimum of 8 years of relevant experience
- Excellent oral and written communications skills
- Strong inter-personal and people management skills
- Strong project management skills
- Access to transportation to attend various meetings held in proximity to the Takeda offices
- Able to fly to various meetings at investigator, vendor or regulatory agency sites
