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Provide statistical support for Takeda preclinical campaigns for design and analysis in the discovery and development of targets and molecules for one or more disease areas. Collaborate with Computational Biology, Pharmacokinetics, and Safety scientists to explore methods and implement discovery strategies to enable data-driven decision making. Apply frequentist, Bayesian, ML/AI fit-for-purpose statistical analyses across various projects and data types. Serve as an expert and mentor in Quantitative Sciences group within implementing statistical development strategies using statistics and cross-disciplinary integrative data analytics.
Job Responsibility
Lead implementation of SQS strategies and ensure deliverables by representing data science function on project teams in support of preclinical studies throughout the drug discovery units and supporting functions
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, promoting, 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
Requirements
Master's degree or higher in statistics or related field
Good English communication skill in both written and verbal
High level of knowledge, expertise, and experience in biostatistics
High capacity for collecting information
Expert-level knowledge of data science programming languages (SAS, R, Python, or similar) and experience with recommended software development practices
Ability to work independently on complicated datasets, covering all aspects of data analysis
High level of expertise and experience in the pharmaceutical industry
Ability to judge regulatory risk and feasibility
Capacity to build statistical strategies for non-clinical work with fresh perspectives
Preparation for future business domains, such as AI/ML and Real-World Data
Strong communication and negotiation skills to lead non-clinical projects
What we offer
Allowances: Commutation, Housing, Overtime Work etc.
Salary Increase: Annually
Bonus Payment: Twice a year
Holidays: Saturdays, Sundays, National Holidays, May Day, Year-End Holidays etc. (approx. 123 days in a year)
Paid Leaves: Annual Paid Leave, Special Paid Leave, Sick Leave, Family Support Leave, Maternity Leave, Childcare Leave, Family Nursing Leave
Flexible Work Styles: Flextime, Telework
Benefits: Social Insurance, Retirement and Corporate Pension, Employee Stock Ownership Program, etc.