Monitoring, Evaluation, and Learning Data Analyst

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Position description

Columbia Global advances Columbia University’s engagement with the world through a network of Global Centers located across ten regions — including Amman, Athens, Istanbul, Mumbai, Nairobi, Paris, Rio de Janeiro, Santiago, and Tel Aviv — alongside program and administrative teams based in New York. The Monitoring, Evaluation and Learning (MEL) function supports data-informed decision-making across this decentralized, multi-country network.

Columbia Global connects New York to a network of Centers spanning ten regions around the world, and the Monitoring, Evaluation, and Learning (MEL) Data Analyst sits at the heart of that connection — helping turn information from across this global footprint into insight. Working under the direct supervision of the MEL Director, the MEL Data Analyst keeps data accurate, consistent, and usable across Columbia Global’s entire international portfolio, gaining regular exposure to programs, partners, and colleagues spanning the Middle East, Europe, South Asia, East Africa, Latin America, and beyond.

This is an entry-level position with real room to grow, offering data entry, cleaning, independent data-quality analysis and reporting, and along with managing existing data systems and helping build Power BI dashboards— a skill set increasingly in demand across monitoring and evaluation and the broader data field. Working alongside program teams across New York units and Global Centers worldwide, the MEL Data Analyst builds a strong technical foundation while contributing directly to an organization whose reach spans the globe.

Responsibilities

• Data entry, cleaning, and quality assurance: Enter, clean, and validate quantitative and qualitative program data from multiple sources; independently analyze data-quality issues, evaluate alternative approaches to resolving discrepancies, and determine and apply appropriate corrective actions within established procedures, escalating issues outside those procedures to the MEL Director; maintain accurate, well-documented data files.
• Manage data systems and dashboards: Manage existing databases and Power BI dashboards and underlying data tables; evaluate data structures, reporting methods, and dashboard configurations, and recommend improvements to data integrity, reporting efficiency, and the usefulness of MEL information; assist in building new dashboards as directed by the MEL Director.
• Use AI-assisted tools under guidance: Apply generative AI and other AI-assisted tools, with appropriate oversight, to support basic data cleaning, extraction, and categorization tasks.
• Support coordination with MEL Points of Contact: Help the MEL Director track outstanding items, prepare materials for quarterly MEL meetings, and respond to MEL Points of Contact across NYC units and Global Centers; investigate non-routine data or reporting issues they raise, identify root causes, and develop recommendations for resolution.
• Maintain data documentation: Keep data dictionaries, process documentation, and file structures organized and current to support consistent data practices across the MEL function.
• Prepare MEL reporting and analysis: Compile, analyze and interpret data for standard and ad hoc program reports and dashboards; identify trends and insights for the MEL Director’s review and use in assessing program performance.
• Perform other duties as assigned.

Qualifications

Bachelor’s degree in data science, statistics, information systems, public health, or a related field.

1–2 years of professional experience in data entry, data management, or a related support role.

• *Applicants must submit a cover letter and resume. **

Preferred Qualifications

• Proficiency in Excel.
• Working knowledge of Power BI or a similar data visualization tool, including experience building or maintaining dashboards.
• Ability to analyze data quality issues, evaluate alternative solutions, and apply corrective actions within established procedures, escalating matters outside those procedures appropriately.
• Experience with data-collection platforms (e.g., Qualtrics, REDCap, KoboToolbox) or similar tools.
• Exposure to SQL or basic coding/scripting.
• Experience using generative AI tools for everyday data or office tasks.
• Interest or coursework in monitoring and evaluation, international development, or higher education settings.
• Strong attention to detail and organizational skills.
• Effective written and verbal communication skills.

Application instructions

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