SAS生物统计程序员 上海

月薪： 1-1.5万/月

该公司所有职位
  • 无工作经验
  • 本科
  • 招若干人
  • 11-09 发布
  • 五险一金
  • 补充医疗保险
  • 补充公积金
  • 餐饮补贴
  • 通讯补贴
  • 交通补贴
  • 绩效奖金

职位描述

职位描述： PURPOSEProvide programming support as part of the Statistical Programming (SP) team to develop and maintain programs to meet internal and external clients’ needs. Support the development of project-related solutions to a variety of statistical programming tasks.RESPONSIBILITIES？ Program, test, and document statistical programs for use in creating statistical tables, figures and listings.？ Program, test, and document analysis datasets (derived datasets) and transfer files for internal and external clients.？ Program quality control checks for the source data and report the data issues periodically？ Assist in development of programming documentation including plans and specifications, as appropriate, under supervision.？ Assist in developing, implementing and validating new process technologies, macros and applications, under supervision.？ Assist project lead in fulfilling project responsibilities.REQUIRED KNOWLEDGE, SKILLS AND ABILITIES？ Basic knowledge of statistics and/or clinical drug development process？ Basic knowledge of Base SAS, SAS/STAT, SAS Graph and SAS Macro Language？ Basic knowledge of applicable clinical research regulatory requirements; i.e., Good Clinical Practice (GCP) and International Conference on Harmonization (ICH) guidelines？ Organizational and communication skills？ Ability to effectively handle multiple tasks, under supervision？ Aptitude for mathematical calculations？ Accuracy and attention to detail？ Ability to establish and maintain effective working relationships with coworkers, managers and clients 职能类别： 临床数据分析员

联系方式

枫林路388号枫林国际大厦A座3楼

公司信息

QuintilesIMS pioneered the idea of helping pharma companies conduct objective clinical trials to establish not only whether a drug is effective, but who can take it safely. Our customers have relied on us to design and conduct rigorous clinical research for decades, from small studies to multinational mega-trials. However, we continue to develop new ways of interpreting and evaluating data that allow us to create more effective trials and determine outcomes faster. If that is your passion, we have a place for you.

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