Evidence Action's mission is to fill the gap between what is effective in global health and development and what is implemented at scale. One of our flagship programs is the Deworm the World Initiative, which envisions a world where all at-risk children have improved health, increased access to education and better livelihoods potential as a result of being free of intestinal worms.
The Associate Program Data Management will support the digitization of data collection tools in SurveyCTO and other electronic platforms, assisting with programming of survey logic, validations, and constraints.
The role provides support to data collectors during fieldwork, including troubleshooting technical issues and flagging data quality concerns.
She / he will execute data cleaning, processing, and management tasks, ensuring proper documentation and adherence to established protocols.
The Associate will assist in maintaining data quality assurance systems and contribute to the generation of descriptive statistics and data summaries as needed.
The ideal candidate will be detail-oriented, systematic, and able to handle multiple data streams while maintaining high standards of accuracy and documentation.
This position will be an integral part of the Data Analytics and Learning team that operates within Evidence Action's broader Monitoring, Learning, and Evaluation (MLE) team.
In this role, the Associate will report to the Senior Associate, Program Data Management, receiving guidance on data processes, contributing to team deliverables, and developing technical and professional skills.
Responsibilities
Support Development and Digitization of Data Collection Tools:
Assist in digitizing data collection instruments in SurveyCTO and other electronic platforms under the guidance of the Senior Associate.
Examples of activities:
Digitize questionnaires in SurveyCTO or other electronic data collection platforms
Program survey logic, skip patterns, validations, and constraints as directed
Test electronic forms and document any errors or issues identified
Support development of activity trackers for MLE and program teams
Troubleshoot basic technical issues with electronic forms.
Provide Fieldwork Support:
Assist with technical support to data collectors during fieldwork under the supervision of the Senior Associate.
Examples of activities:
Monitor incoming data submissions and flag issues to the Senior Associate
Assist in troubleshooting technical problems with electronic forms during data collection
Document data quality issues identified during fieldwork
Support communication with field teams on data corrections needed.
Execute Data Quality Assurance Tasks:
Implement quality checks and validation processes to support data integrity under the guidance of the Senior Associate.
Examples of activities:
Run validation scripts to check completeness, cleanliness, and consistency of program data
Conduct data cross-validation across multiple sources as directed
Document and report data quality issues to the Senior Associate
Support maintenance of quality assurance tools and dashboards
Track recurring data quality issues and maintain documentation.
Execute Data Processing and Cleaning:
Carry out data cleaning, processing, and management tasks following established protocols and procedures.
Examples of activities:
Clean, process, and prepare datasets for analysis and reporting
Document all data cleaning processes and steps completed
Support data collation from multiple sources into unified datasets
Ensure secure storage and organized filing of program data
Assist in preparing clean datasets for dissemination to stakeholders.
Support Data Analysis and Reporting:
Contribute to basic analysis and reporting tasks as assigned.
Examples of activities:
Generate descriptive statistics and summaries from program data
Assist in preparing data visualizations for program reporting
Flag data anomalies or emerging trends to the Senior Associate
Support preparation of analytical outputs as directed.
Support Data Systems Maintenance:
Assist in maintaining databases and data management systems that support program monitoring and evaluation needs.
Examples of activities:
Support maintenance of program databases
Generate passlists and create verification IDs for program activities
Assist in data integration tasks across systems
Support management of multiple data streams across Evidence Action's programs.
Support Capacity Building Activities:
Assist in training and capacity building activities for data management.
Examples of activities:
Assist in conducting data quality training for staff involved in data collection
Support development of training materials and standard operating procedures
Help facilitate refresher trainings based on identified quality gaps.
Contribute to Administrative and Departmental Operations:
Support departmental operations as needed.
Examples of activities:
Support administrative tasks as assigned by the Senior Associate
Assist in tracking deliverables and deadlines
Perform other data management tasks as assigned by supervisor.
Requirements
Minimum Bachelor’s Degree in economics, statistics, or any other relevant field
Minimum of 2 - 3 years of experience in quantitative research methods and data management, preferably with large and/or complex datasets.
At least 1-year full time experience conducting data cleaning using Stata, R, Python or MatLab for large datasets (mandatory)
Experience in working with and programming data entry interfaces using a variety of applications both purchased and open source.
Knowledge of SurveyCTO, CSPro, ODK, KoBo and Access will be an added advantage (SurveyCTO and/or ODK highly preferred)
Well conversant with the use of MS Office applications especially Excel.
Ability to work under pressure in a working environment that changes suddenly to accommodate new data needs
Strong interpersonal and communications skills to work effectively with a team that is geographically dispersed.
Self-directed/self-motivating personality, with proven ability to manage demands from multiple supervisors while adhering to program deadlines and priorities.
Strong critical and analytical thinking skills.
High attention to details and well organized.
Should have real passion of working with data, be able to think and tell a story from the data (Key desirable)
Intellectual flexibility and willingness to form and adjust opinions based on evidence
Quick to learn, motivated to self-teach and capable of independently translating new knowledge into practice.