Analyst (Biostatistician/ Statistician), Pathology and Laboratory Medicine - Karachi, Pakistan

Company Name

Job Functional Area

Job Title
Analyst (Biostatistician/ Statistician), Pathology and Laboratory Medicine

Job Location

Degree Title
Masters degree in Statistics

Minimum Experience
2 Years

Posted on
Nov 29, 2020

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Job Description

Aga Khan University invites applications for the position of Analyst, Department of Pathology and Laboratory Medicine.

Responsibilities:
You will be expected to:
provide statistical expertise to support the synopsis and dissertation based research being conducted in the department, which includes study design and analysis of surveys, longitudinal studies, cluster randomized trials and experimental study design.
perform sample size, power calculations and WHO calculator
develop statistical analysis plans and reporting formats, and perform complex statistical analyses
check data for inaccuracies, conduct data cleaning, data management and big data mining
prepare derived datasets for the analysis using statistical packages, preferably Stata 14, SPSS 21, AMOS.
contribute to the interpretation and publication of research results and prepare reports for interim and final analysis for manuscripts.
coordinate with the project teams and independently manage all complex statistical aspects of a project
keep abreast of new statistical methods and comply with all institutional policies as well as regulatory requirements for the programming, analysis and reporting of research projects.

Requirements:
You should have:
at least a Masters degree in Statistics with two years of relevant experience of working in a large reputable public health or health care organization
excellent command on SPSS, Stata and other statistical packages, preferably with some knowledge of database management and computer programming
proficiency in spreadsheets and power point presentations
excellent interpersonal skills, particularly communication skills
ability to effectively work with diverse teams as well as independently

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