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This newly created position will report to the Head of Learning, Monitoring & Evaluation, and Data Management. They will be the primary member of the Monitoring, Evaluation & Learning (MEL) team responsible to supporting data-related tasks in the team. He/She will be a generalist and support MEL and Programme staff on analysis, data engineering, and, in some cases, data science. He/She will be responsible for setting up data management systems, supporting on other data-heavy and data science issues, and extracting meaning and learning from data, in order to demonstrate project progress and performance, and to evaluate research hypotheses. For the latter, He/She will provide advanced analysis and visualisation, and contribute or lead on the written interpretation of the analysis.
Data Engineering & Data Management
- Develop and maintain data management pipelines using APIs and cloud computing resources (Microsoft Azure).
- Maintaining local and cloud databases and managing API/scripting links to other applications like PowerBI.
- Create and maintain documentation and training materials for data systems.
- Support Data Scientists on development and deployment of machine learning models.
- Manage and download data from online data collection platforms, e.g. KoboCollect, ONA, Commcare.
- Data quality checks during surveys, including setting up scripts in Python or R to automate these.
- Cleaning of data sets, including tasks like: matching records between databases, outlier identification, categorisation of written answers, reformatting/standardising responses, removing duplicate records, etc.
- Applying appropriate analysis techniques to extract meaning from data, including calculating relevant statistics and pivot tables.
- Producing understandable, informative, and well-formatted graphs and visualisations to clearly demonstrate results of analysis.
Support to programmatic MEL
- Contribute to MEL system design: hypotheses, logic models, questionnaires
- Provide written interpretation of analysis findings in reports or PowerPoint presentations
- Support the design and development of MEL technologies that will be used to collect, store, analyse, and visualise data – within single programmes or across the MC-E4I portfolio. This include systems that are cloud-based.
Reports Directly To: Head of Learning, Monitoring & Evaluation, Learning, and Data Management
Works Directly With: MEL team, and Programme teams where data & analyses are being generated.
Accountability to Participants and Stakeholders
Mercy Corps team members are expected to support all efforts toward accountability, specifically to our program participants, community partners, other stakeholders, and to international standards guiding international relief and development work. We are committed to actively engaging communities as equal partners in the design, monitoring and evaluation of our field projects.
Minimum Qualification & Transferable Skills
- 4 to 6 years professional experience with data analysis
- Specific experience setting up and maintaining cloud-based data management systems, Microsoft Azure preferred though not required
- Proven experience conducting thorough and quality analysis of survey data sets
- Bachelor’s degree required, Master’s preferred
- Excellent organizational skills including attention to detail and multitasking skills
- Excellent proficiency using Excel and a data-related scripting programming language (Python preferred, R & Stata desired)
- Working on analysis of data sets that relate to energy in humanitarian or development contexts
- Experience developing and deploying machine learning and other statistical/optimisation models
- Work in contexts around Africa and internationally
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