Job Expired
Laterite (Ethiopia) Ltd.
Natural Science
Statistics
Addis Ababa
1 years
1 Position
2022-08-25
to
2022-09-30
Computer sciences
Economics
Statistics
Full Time
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Job Description
Country: Ethiopia
Organization: Laterite
Closing date: 30 Sep 2022
Laterite is a data, research, and technical advisory firm specialized in complex development challenges. We work with universities, global think tanks, international NGOs, multilateral donor organizations, and government ministries and agencies. Our clients include, for example, the World Bank, USAID, TechnoServe, Promundo, the Mastercard Foundation, and several UN agencies.
We currently have offices in the Netherlands, Rwanda, Ethiopia, Kenya, Uganda, and Tanzania. The team brings together more than 70 full time local and international staff, as well as 1,000+ enumerators across all countries. We are proud to be a culturally diverse organization, and we welcome applications from groups currently under-represented in our team. Learn more: www.laterite.com
We work in socio-economic development research projects. We believe that impact is a long-term endeavour that requires being embedded in the local context. Delivering high-quality research requires building local teams and data collection systems, knowing the country, and establishing close working relationships.
One of Laterite’s key strategic goals is to create a collaborative and rewarding working environment for our staff, where every team member feels engaged, represented, and heard. Laterite is committed to create opportunities for learning and career development within the team and across our offices.
Laterite is committed to creating a diverse environment and is proud to be an equal opportunities employer. All qualified applicants will receive consideration for employment without regard to race, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age or veteran status.
Job Description & Key Responsibilities
The Data Quality Analyst position is based in Addis Ababa, Ethiopia. Data Quality Analysts at Laterite play a hands-on role in the implementation of projects by ensuring that relevant quality control measures are in place at all key stages of a project, from research instruments coding to data collection processes to incoming data monitoring. Other responsibilities include contributing to the improvement of the current quality control processes and tools.
Key responsibilities:
Project-based responsibilities
Codes research instruments and reviews them to ensure internal flow and consistency.
Creates/adapts project specific monitoring tools.
Trains audit enumerators on project specific monitoring tools.
Conducts regular quality checks on incoming data and shares feedback with project lead in the Data Team.
Cleans and further processes incoming data.
Reports on the progress of assigned tasks to the Data Quality Associate.
Quality-team based responsibilities
Contributes to the development of different data processing and monitoring tools. These tools should be efficient, effective and to the maximum extent automated.
Works closely with other teams within Laterite to ensure quality control at the different stages of a research project cycle.
Builds efficient internal systems for the management of Laterite’s resources and assets.
Minimum qualification and requirements
At least 1 year of work experience in a data heavy role.
Bachelor’s degree in Economics, Statistics, Engineering or related field.
Familiarity with statistical analysis and related tools/software (in particular Stata).
Excellent oral and written communications in English and Amharic (any other local language is a plus).
Must be an Ethiopian national
Application Process
The first step is to complete a 30-minute numeracy and literacy assessment for which no special preparation is needed.
Link to assessment: https://form.jotform.com/222284158603555
Successful candidates will then be invited to upload their CV and cover letter via our online application system.
Fields Of Study
Computer sciences
Economics
Statistics
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