Associate Director, Statistics, Data Science応募後で応募 求人ID R0025076 掲載日 11/17/2020 Location:Boston, Massachusetts
- Provide leadership and expertise in analytical support of real-world data research, outcomes research, biomarkers, digital solutions and artificial intelligence/machine learning (AI/ML) projects.
- Drive implementation of data science strategy for safety and health-value research to ensure that analytical methodologies are acceptable to regulatory agencies and publications.
- Provide leadership and expertise in development and implementation of innovative analytical tools, utilities and standards for data analyses of both clinical trial and real-world data.
- Provide technical expertise in system security and technical support for data transparency and disclosure
- Represent the function in company-wide data science initiatives. Lead the initiative execution and delivery strategies related to both risk identification and effective mitigations.
- Lead and accountable for multiple data science projects in an assigned area.
- Enable the tactical execution of the SQS and DSI vision and mission.
- Proactively implement delivery strategies to incorporate data science research to clinical development.
- Drive and implement process efficiency and improvements for management of real-world databases by collaborating with outside vendors and internal stakeholders.
- Lead development of innovative solutions and standards for generating analyses datasets for common analyses from various data sources such as EHR and claims.
- Provide mentorship, matrix or direct management of small team of SQS colleagues
- Represent the function in external professional initiatives and organizations to identify industry best practice and increase the visibility of Takeda.
- Ensures compliance of function with Takeda SOPs, standards and all applicable regulations.
- PhD in Computer Science or related field with 5+ years of data science programming and development experience; or MS in Computer Science or related field with 8+ years of relevant experience; or BS in Computer Science or related field with 10+ years of relevant experience.
- Strong project management and communication skills.
- General knowledge of statistical and data mining techniques (regression, decision trees, clustering, neural networks, etc.)
- General knowledge of SAS programming language and core SAS software.
- Expert knowledge of common programming and computing principles, strong experience with operating systems including Unix, Linux, and Windows; expertise in office software.
- Experience in developing programming tools and utilities and implementing global analysis systems within bio-pharmaceutical industry
- General understanding of regulations on computerized systems used in clinical trials and big data analyses, software development lifecycle and validation of computer tools and utilities
- Working knowledge of data flow in clinical trials and real-world databases
- Good knowledge of FDA, EMEA and ICH regulations and industry standards applicable to clinical study data and reporting on clinical trials, including data standards for electronic submissions, e.g. CDISC standards.
- Ability to work independently on complicated data science projects.