Statistician Job at Chemonics International

[Jobrib]

Job Title: Statistician

Location: Lagos, Nigeria

Employer: Chemonics International

Roles:

•   Develop a sound sampling framework for carrying out performance evaluation with respect to the states covered by the program as well as value chain commodities.

•   Critically design a recommended and justifiable sample size that is more cost-effective and also provide accurate results for impact assessment.

•   Work with M&E team to develop a recommended data collection manual based on the project's approach and operational methodology.

•   Where necessary, provide trainings for the M&E team on sampling methodologies and frameworks for the program. The training should among other things cover sample size, confidence level, confidence interval, sampling error, etc.

•   Using existing information develop an appropriate sample size for the annual cost, yield and income survey.

Qualifications/Experience:

•   A minimum of Master's Degree in Statistics, Mathematics, Social Sciences with professional training and working experience in statistical sampling design.

•   Experience in designing sampling frameworks for large projects, AgriCUltural and value chain indevelopment context will be added advantage

•   At least 5 years demonstrated progressive experience in program statistical design in thecontext of a development project.

•   Excellent understanding and applications of computerized database development, system,processes and applications;

•   Demonstrable skills and experience in development of data tools, data analysis, data qualityassessments, and data use;

•   Past experience in use and applications computer based field data collection techniques:

Deliverables: At the end of the assignment, the statistician will be expected to submit A detailed report showing sampling methodology highlighting recommended sample size for each of the value chains based on population, state, sampling error, and level of distribution. The report should also elaborate on data collection methodology using the preferred/recommended sampling methodology.

Deadline: 19.09.2013

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