OVERALL JOB PURPOSE:
This post is required to lead statistical analyses and provide statistical support for the CHAIN Network and allied clinical trials and mechanistic studies, including laboratory, epidemiological, clinical trials, health systems and social science research.
REPORTS TO: Principal Investigator
DIRECTLY SUPERVISES: None
INDIRECTLY SUPERVISES: None
KEY RESPONSIBILITIES:
Undertaking statistical analyses of data collected by the CHAIN Network, allied trials and mechanistic studies in collaboration with scientists working on these projects in Kenya and abroad.
Providing statistical support in the form of advice to researchers in the CHAIN Network and working on allied trials and mechanistic studies regarding protocol development, analysis plans and issues encountered during analysis.
Curating requests for data and analyses and liaising with sites and investigators over request to ensure appropriate communication, adherence to policies and avoidance of duplication.
Helping in developing policy on database and data entry platforms, and ensuring their accuracy and security, for use by CHAIN and allied clinical trials.
Working closely with the data management teams for CHAIN and allied trials on the implementation of data systems
Membership of the Centre Scientific Committee
Supporting collaborations to deliver statistical training in partnering Universities and institutions.
QUALIFICATIONS:
A PhD in Statistics or Epidemiology or a related field
Master’s degree in Statistics or mathematics.
Experience in statistical analysis of major projects with outputs published in peer-reviewed journals.
Experience in leading survival, clinical trial or cohort analyses
Ability to network, build and maintain strong relationships with. Team members in Kenya and overseas
Willingness to respond within tight timelines and to cope with changing assignments
Computer literacy with proficiency in Microsoft applications
DESIRABLE CRITERIA:
Experience of work within large international networks
Experience of analysis of infectious diseases and nutrition data
Experience/ training in statistical analysis software (such as R, SAS, SPSS or STATA) and analysis of large and complex data files.
COMPETENCIES:
Strong data management and analysis skills
Attentive to detail
Confidentiality and integrity
Excellent interpersonal and communication skills
Team working and ability to work in a multi-cultural environment
