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AD-Statistics and Data Management

Lieu Pékin, Municipalité de Pékin, Chine Job ID R-119218 Date de publication 09/15/2021
  • The AD is Stat, DM, RWE and HEOR management role to ensure evidence generation goals are achieved. Accountable and responsible for providing statistic, data management, RWE/HEOR and scientific expertise in designing, generating, synthesizing, and communicating evidence based data to support product launch, pricing, reimbursement, and clinical differentiation. Acts as leader and manager by providing coaching and implementing internal standards and processes.
  • Responsibilities:
  • Continuously acquire and update necessary scientific knowledge on statistics, data management, RWE and therapeutic areas
  • Recruit the right talent for the role of statistician, data manager, and RWE talents based on scientific or technical ability, business acumen, communication skills and positive attitude
  • Conduct one on one meeting to coach and review capabilities of the managed functions
  • Retain and develop high performing talents through ongoing development
  • Develop individual and team accountability
  • Identify areas for self-development and discuss developmental needs with line manager using the 70-20-10 principle (experiential learning, coaching/networking/relationship-based learning and class room training)
  • Attend & actively participate in learning programs, training, projects and meetings (where needed)
  • Design and interpret Non-intervention studies and Phase IV studies in collaboration with medical advisor, safety physician and other stakeholders including the Medical Evidence and Outcome Research (MEOR.
  • Design and undertake high quality RWE projects/studies in collaboration with Market Access and global P&RWE, to demonstrate evidence of efficiency in support of the product commercial, market access and medical objective.
  • Provide local scientific expertise in proposal and protocol review for External sponsored scientific research (ESR).
  • Interpret product data appropriately by internal and external training, to promote appropriate drug use, in alignment with external activity.
  • Early and comprehensive engagement of KOL in research design.
  • Provide effective trainings to medical advisors & MSLs to improve their capability on study design & interpretation.
  • Identify and communicate best practices.
  • Ensure strategies transfer to skill and knowledge development for Medical Affairs leaders
  • Requirements:
  • (a) Organization structure / 组 织 机 构
  • ( Please attached an updated organization chart of your team 请 附 上 你 所 属 团 队 的 最 新 结 构 图)
  • - Functionally reports to / 功 能 汇 报 (Please specify position title 请 注 明 职 位 名 称)
  • • Associate Director, Evidence Generation
  • - Operationally reports to / 运 作 汇 报
  • • Associate Director, Evidence Generation
  • - Position title of subordinates/ Number of subordinate / 下 属 的 岗 位 名 称 及 人 数
  • • Associate project manager, Project manager, Sr. Project manager, CTA/assistant if needed or applicable
  • (b) Key working relationships / 主 要 工 作 关 系
  • - Internal contacts within AZ / 内 部 联 系
  • • Brand Team (Brand Physician), MSL, Publication manager, Statistician
  • • Clinical Research Team
  • • Sales Force
  • • Global Product Team
  • • Local CPrM / QA/Financial Team
  • • Local drug supply chain
  • • Sales Training team
  • • GMD, GMA, Global ESRO, etc
  • • Finance
  • • Procurement
  • • Marketing team
  • • RA
  • • Manufactory
  • - External contacts with organizations outside AZ / 外 界 联 系
  • • Key Opinion Leaders
  • • Principal Investigator/Co-Investigators
  • • CRO
  • • Central Lab
  • • Vendor for drug supply management
  • • Any other vendors if related to post-marketing study
  • (c) Job requirements /工 作 要 求
  • Academic / Professional qualification / 学 历 / 专 业 资 格
  • MS/MSc degree essential and PhD desirable in statistics, epidemiology, health economics or related discipline
  • Technical / skill training / 技 术 / 技 能 训 练
  • Thorough knowledge and experience in regulatory regulation and drug development
  • Full expertise in applied statistics and data management
  • Ability to interact and manage a range of stakeholders both internally and externally
  • Strong self-management and execution ability
  • Coaching & Feedback, Leadership skills
  • Working experience (No. of years / 年 资, Job function / 工 作 功 能, Business types / 业 务 种 类 )
  •              Essential     必 需  
  • Significant years industrial experience at multinational pharmaceutical company or Clinical Research Organization (CRO) as a senior biostatistician
  • Cross-functional experience in drug development, particularly study design and interpretation skills
  •              Desirable    理 想
  • Knowledge in observational studies and/or real world evidence
  • Language ability / 语 言 能 力
  • Fluent in speaking and written English
  • Computer literacy / 电 脑 知 识      
  • PC/Windows application
  • Others / 其 他
  • Qualified to apply for China Merchants Bank Credit Card (Business expenses should be reimbursed through company credit card)
  • AstraZeneca is an equal opportunity employer. AstraZeneca will consider all qualified applicants for employment without discrimination on grounds of disability, sex or sexual orientation, pregnancy or maternity leave status, race or national or ethnic origin, age, religion or belief, gender identity or re-assignment, marital or civil partnership status, protected veteran status (if applicable) or any other characteristic protected by law.

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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