Position Summary:
The Data Associate plays a crucial role in ensuring the provision of accurate, timely, and dependable data to guide project execution, monitoring, and strategic decision-making. In collaboration with the Technical Program Manager and MEL Lead, the position is dedicated to enhancing data collection, validation, analysis, and reporting procedures in accordance with established MEL frameworks and US data quality standards.
This role plays a key part in sustaining robust data systems, generating analytical deliverables and visual representations, and facilitating field data collection alongside stakeholder engagement. Ideal for an emerging professional, it demands proficiency in quantitative analysis, meticulous attention to detail, and the capacity to convert data into practical insights that drive program effectiveness and adaptive management strategies.
Oversee and execute essential duties and responsibilities as part of the core operational framework. Lead and coordinate critical tasks to ensure alignment with organizational objectives and strategic goals. Develop and implement processes that enhance efficiency, productivity, and overall performance across designated responsibilities. Monitor progress, evaluate outcomes, and provide actionable insights to refine workflows and optimize results. Collaborate with cross-functional teams to achieve seamless integration of initiatives and maintain high standards of accountability. Ensure adherence to established policies, procedures, and compliance requirements while fostering a culture of continuous improvement.
Guarantee the punctual, thorough, and precise gathering of data from project locations and collaborators, adhering strictly to Monitoring, Evaluation, and Learning (MEL) frameworks and established reporting schedules.
Conduct systematic data cleaning, validation, and verification to uphold data quality and integrity; promptly address and resolve any discrepancies in collaboration with data providers.
Ensure datasets and data systems are meticulously organized, secure, and current to support seamless access, accurate reporting, and efficient audits—including preparation for Data Quality Assessments (DA).
Support the execution of ongoing data analysis and the creation of summaries, dashboards, and visualizations using tools such as Excel, Superset, and DHIS2 to guide programmatic decision-making.
Facilitate accurate and efficient data entry, extraction, and reporting processes to ensure full compliance with project specifications, national standards, and donor expectations.
Conduct field data collection initiatives, including surveys, interviews, and validation exercises, to enhance data accuracy and ensure comprehensive coverage.
Monitor project metrics, deliverables, and milestone progression in relation to established targets and schedules; identify and escalate potential risks, bottlenecks, and data inconsistencies promptly.
Prepare routine progress updates and reports, analyzing performance trends, identifying issues, and documenting corrective actions to ensure clear communication and informed decision-making.
Assist in establishing and implementing standardized tools, SOPs, and reporting templates to enhance data management practices and ensure consistency across processes.
Collaborate closely with project teams and external partners to facilitate the seamless transmission of data, ensure adherence to reporting requirements, and leverage information to support informed decision-making.
Ensure seamless coordination and administrative assistance for data-focused meetings, training sessions, and stakeholder interactions.
Required qualifications include a bachelor’s degree in computer science, engineering, or a related field, along with a minimum of three years of professional experience in software development. Proficiency in programming languages such as Python, Java, or C++ is essential, as is experience with database management systems and cloud computing platforms. Strong problem-solving skills and the ability to work collaboratively in a team environment are also necessary. Familiarity with agile methodologies and version control systems like Git is preferred.
A bachelor’s degree in Statistics, Data Science, Actuarial Science, Public Health, or a related field with a quantitative focus is required.
Proven expertise in advanced Microsoft Excel, coupled with a practical understanding of data visualization and reporting tools such as Power BI, Superset, and DHIS2.
Skilled in cleansing, validating, and structuring quantitative and qualitative datasets to ensure accuracy and readiness for analytical processes.
Proficiency in utilizing digital data collection tools, data entry platforms, and routine data management systems is required.
Demonstrates a strong capability to assist with research initiatives, conduct field data collection, or perform analytical tasks in a well-defined program framework.
Experienced in meticulously examining documentation, compiling detailed reports, and coordinating with stakeholders to validate the thoroughness and precision of data.
Maintains meticulous attention to detail while ensuring adherence to rigorous data quality standards.
Demonstrates strong organizational and time management capabilities, effectively handling competing priorities and consistently meeting established deadlines.
Proven ability to communicate clearly and effectively while fostering strong interpersonal relationships, enabling seamless collaboration within cross-functional teams.
Highly motivated, resourceful, and flexible, capable of working autonomously while demonstrating strong initiative in a fast-paced, outcome-driven setting.
Proficiency in statistical software, such as R, STATE, or Python, is considered a valuable asset for this role.
Qualifications
BA/BSc/HND
