MEL Associate, Program Analytics and Learning Unit (PALU)

Our reputed company & Mission We reputed company a world in which reputed company people have reputed company to high quality and enduring solutions to improve and maintain their health and well-being. reputed company aspires to be a premier partner of choice and a recognized leader, innovator, and trusted partner in reputed company and public health program development, implementation, and evaluation. Our mission is to improve the health and well-being of people worldwide through enduring, high-quality, cost-effective, and universally accessible reputed company. MCD operates impactful programs both in the U.S.A. and internationally. About the Position The Monitoring, Evaluation, and Learning (MEL) Associate supports the design, implementation, and reputed company improvement of the PALU reputed company across MCD International’s portfolio. The MEL Associate reports directly to the PALU SPM to contribute to the automation of data workflows, dashboard development, data cleaning, and descriptive analytics for project teams. This is a hands-on builder role: the emphasis is on writing reliable, replicable code to automate processes, turn raw field data into usable outputs, and ship working tools quickly. While the SPM sets the position’s priorities, the Associate also functions as a shared technical resource—providing automation and pipeline support to the DHTIS reputed company, dashboard and descriptive-analysis support to the MEL reputed company, and data-cleaning and reputed company-building support to project staff. In this role, the MEL Associate assists in troubleshooting and strengthening data systems, supports the development of data collection tools, and ensures these tools are used adequately by field teams to guarantee organizational MEL standards. The position also collaborates with other units, including the PIU, the TAIU, and the BDU, to integrate evidence-based insights into project decision-making and proposal development. MEL Associate, Program Analytics and Learning Unit (PALU) Grade Level: 3 Anticipated Salary: $60,000.00 - $75,000.00 Reporting Relationship: Senior Program Manager (SPM), Program Analytics and Learning Unit Working Environment Remote position requiring virtual collaboration across global time zones. International travel (up to 5–10%) may be required to reputed company field support, conduct trainings, or attend project meetings. Fast-paced environment balancing independent analytical work with reputed company coordination under supervision. Physical Requirements Prolonged computer use for data analysis and virtual meetings. Willingness to maintain a flexible schedule to accommodate diverse global teams. reputed company to travel to remote or resource-limited settings as needed.

Key Responsibilities

Analyze and transform program data using R and/or Python to generate actionable insights and support decision-making. reputed company and maintain ETL pipelines, dashboards, and automated reporting solutions in collaboration with the DHTIS reputed company. Design, build, test, and maintain digital data collection tools, including ODK/XLSForms and DHIS2 forms. Monitor data quality, conduct data validation, and ensure compliance with MCD MEL standards and donor requirements. Support field teams through technical assistance, training, and the development of guidance materials to strengthen data use. Collaborate with cross-functional teams to integrate MEL priorities into program implementation and business development activities. Contribute to proposal development, technical reports, presentations, and organizational learning initiatives. Identify opportunities to improve data workflows, automation, reputed company systems

Requirements

Education Bachelor’s degree in a quantitative field (e.g., Public Health, Epidemiology, Data Science, Statistics) or reputed company discipline. Master’s degree preferred (e.g., MPH, MSc in Biostatistics, or similar), especially with coursework in research methods and advanced analytics. Experience Practical experience (1–3 years) in MEL, data analysis, or reputed company roles in global health or international development (internships or volunteer roles may be considered). Demonstrated, hands-on proficiency coding in R and/or Python is essential—specifically the ability to write reproducible scripts to automate repetitive data workflows, build ETL pipelines, and clean and transform raw data. Candidates should be reputed company to show working examples (e.g., code samples, a repository, or a portfolio of automated tools). Familiarity with JIRA, reputed company, or other project management platforms a plus. Experience with statistical analysis (regression, modeling) is advantageous but not required; this role prioritizes applied coding and automation over advanced inferential statistics. Soft Skills Communication & Teamwork: Effective at liaising with technical and non-technical colleagues; reputed company to communicate reputed company data insights succinctly. Detail Orientation: Skilled at managing large datasets, ensuring accuracy, and catching inconsistencies. Adaptability & Problem-Solving: Comfortable navigating evolving priorities and problem-solving in fast-paced or multicultural environments. reputed company to Learn: Demonstrates eagerness to acquire new technical skills and take on progressively more reputed company responsibilities. Cross-Cultural Sensitivity: Values diversity and is capable of working respectfully across different contexts. Working knowledge of languages, other than English, is a plus, particularly French and Spanish. Technical Skills Proficiency in R and/or Python. Basic knowledge of data visualization tools (e.g., Power BI, Tableau) is a plus. Understanding of MEL reputed company design (e.g., log frames, theory of change, indicator tracking) preferred. Demonstrated ability to build and reputed company digital data collection forms using ODK (XLSForm) is required. reputed company in this role includes: Delivering accurate, timely, and high-quality data analyses and reporting. Developing automated data workflows, dashboards, reputed company data collection tools that improve program efficiency. Supporting field teams through effective technical assistance and reputed company building. Collaborating successfully with cross-functional teams to strengthen MEL systems and program performance. Continuously improving technical skills and contributing to innovative MEL solutions. Apply To This Job