Intern, Field Operations, MLE at Evidence Action

Job Description

About Monitoring Learning and Evaluation (MLE) Team

• The MLE team embodies the evidence-based nature of Evidence Action’s work and enables the organization to be a data-driven organization. The team provides services across Evidence Action Africa region in meeting the following outcomes:
• Ensure all ongoing program monitoring needs are met (including M&E design and quality data collection)
• Programs have access to timely and useful data for day-to-day programmatic planning and decision-making
• Analysis and research are conducted to support in program improvements (including operation research, monitoring research and cost-efficiency analysis)
• Support with timely, useful and clear information for evidence-based decision-making (including providing support to connect the dots)
• Support regional leadership in designing new programs and partnerships for exploration and evaluation
• Ensure standards, systems and processes are setup for delivery of all functions (monitoring, analysis, research, information systems and quality data)

Intern Position Overview

• The intern will be a member of the MLE field operations unit responsible for field monitoring, survey data collection, and direct program monitoring support. The person must be organized, systematic, and love working with data. S/he will work closely with other MLE teams to ensure data is collected and used as per the standard operating procedures while adhering to set timelines. This position will be based in Abuja.

Key Tasks & Responsibilities

The key tasks the intern will work on include:

• Assist in the QA/QC of the data collected. This will include reviewing data submitted by independent monitors during data collection for completeness and accuracy. Supporting back-check activities, geo-mapping review and in-field supervision activities, quality of data, and troubleshooting any data errors.
• Survey Testing: supporting the team in testing digitized surveys to ensure they are ready for use in the field.
• Check the completeness of data: The intern will check if the data submitted for analysis is complete and of the needed quality before it is used for analysis. He/she will liaise with the data management team to ensure all data is clean and accurate for analysis
• Support preparatory activities for PMCV: Support the review of materials and documents needed for training and process monitoring.
• Secondary data as needed: The intern will search download and manage any secondary data that might be of interest to the team
• Mapping: Under the guidance of the associate, the intern will develop maps in ArcGIS/QGIS/R to geographically represent program and monitoring information.
• Excel Visual: The intern will develop an automated dashboard in Excel and other software as guided by the senior associate. The visual will be shared with the program team to improve access to and usability of data.
• Any other tasks as assigned by the supervisor.

Requirements

• Bachelor’s degree in economics, statistics, or any other quantitative field.
• Knowledge of data collection, management and analysis tools such as SurveyCTO, DHIS, Stata, Excel etc.
• Basic knowledge of monitoring and evaluation fundamentals
• Basic experience with data collection, data management, and/or analysis.
• High level of competency in developing PowerPoint presentations and presenting them.
• Strong interpersonal and communication skills to work effectively with a team that is geographically dispersed
• Self-directed or self-motivating personality with ability to adhere to program deadlines and priorities
• Strong critical and analytical thinking skills
• Familiarity of geospatial analysis in ArcGIS/QGIS and mobile phone surveys will be an added advantage.
• Intellectual flexibility and willingness to form and adjust opinions based on evidence
• Have a strong commitment to evidence-based practice and data management, as well as analytical skills
• Be enthusiastic to develop personally and professionally as part of a growing team
• Possess a strong attention to detail and a genuine love of working with data