Palladium develops and delivers solutions that create positive impact for communities, businesses, societies and economies. We transform lives and create enduring value by working with governments, corporations and non-profit organisations.

Position Summary:

The Data Associate supports the delivery of high-quality, timely, and reliable data to inform project implementation, monitoring, and decision-making. Working closely with the Technical Program Manager and MEL Lead, the role focuses on strengthening data collection, validation, analysis, and reporting processes in line with established MEL frameworks and US data quality standards.

The position contributes to maintaining effective data systems, producing analytical outputs and visualizations, and supporting field data collection and stakeholder coordination. It is suited for an early-career professional with strong quantitative skills, attention to detail, and the ability to translate data into actionable insights that enhance program performance and adaptive management.

Primary Duties and Responsibilities:

• Ensure timely, complete, and accurate data collection from project sites and partners, in line with MEL plans and reporting timelines.
• Perform routine data cleaning, validation, and verification to maintain high data quality and integrity; proactively resolve discrepancies with data providers.
• Maintain well-organized, secure, and up-to-date datasets and data systems to enable efficient access, reporting, and audits (including DQA readiness).
• Support routine data analysis and generation of summaries, dashboards, and visualizations (Excel, Superset, DHIS2) to inform program decision-making.
• Facilitate data entry, extraction, and reporting, ensuring alignment with project, national and donor requirements.
• Participate in field data collection activities (surveys, interviews, validation exercises) to strengthen data accuracy and completeness.
• Track project indicators, outputs, and activity progress against targets and timelines; flag risks, delays, and data gaps.
• Support preparation of routine progress updates and reports, highlighting performance trends, issues, and corrective actions.
• Contribute to development and use of standard tools, SOPs, and reporting templates to strengthen data management and consistency.
• Coordinate with project teams and partners to ensure timely data flow, reporting compliance, and effective use of data for decision-making.
• Provide logistical and administrative support for data-related meetings, trainings, and stakeholder engagements.

Required Qualifications:

• Bachelor’s degree in Statistics, Data Science, Actuarial Science, Public Health, or a related quantitative discipline.
• Demonstrated proficiency in advanced Microsoft Excel and working knowledge of data visualization and reporting tools (e.g., Power BI, Superset, DHIS2).
• Experience in data cleaning, validation, and preparation of both quantitative and qualitative datasets for analysis.
• Familiarity with digital data collection tools, data entry platforms, and routine data management systems.
• Proven ability to support research, field data collection, or analytical assignments within a structured program environment.
• Experience reviewing documentation, preparing reports, and following up with stakeholders to ensure data completeness and accuracy.
• Strong attention to detail with a commitment to maintaining high data quality standards.
• Demonstrated organizational and time management skills, with the ability to manage multiple priorities and meet deadlines.
• Effective communication and interpersonal skills, with the ability to work collaboratively in multidisciplinary teams.
• Self-driven, proactive, and adaptable, with the ability to work independently and take initiative in a results-oriented environment.
• Working knowledge of statistical software (e.g., R, STATA, or Python) is an added advantage.

• Ensure timely, complete, and accurate data collection from project sites and partners, in line with MEL plans and reporting timelines.
• Perform routine data cleaning, validation, and verification to maintain high data quality and integrity; proactively resolve discrepancies with data providers.
• Maintain well-organized, secure, and up-to-date datasets and data systems to enable efficient access, reporting, and audits (including DQA readiness).
• Support routine data analysis and generation of summaries, dashboards, and visualizations (Excel, Superset, DHIS2) to inform program decision-making.
• Facilitate data entry, extraction, and reporting, ensuring alignment with project, national and donor requirements.
• Participate in field data collection activities (surveys, interviews, validation exercises) to strengthen data accuracy and completeness.
• Track project indicators, outputs, and activity progress against targets and timelines; flag risks, delays, and data gaps.
• Support preparation of routine progress updates and reports, highlighting performance trends, issues, and corrective actions.
• Contribute to development and use of standard tools, SOPs, and reporting templates to strengthen data management and consistency.
• Coordinate with project teams and partners to ensure timely data flow, reporting compliance, and effective use of data for decision-making.
• Provide logistical and administrative support for data-related meetings, trainings, and stakeholder engagements.

• Demonstrated proficiency in advanced Microsoft Excel
• Working knowledge of data visualization and reporting tools (e.g., Power BI, Superset, DHIS2)
• Experience in data cleaning, validation, and preparation of both quantitative and qualitative datasets for analysis
• Familiarity with digital data collection tools, data entry platforms, and routine data management systems
• Proven ability to support research, field data collection, or analytical assignments within a structured program environment
• Experience reviewing documentation, preparing reports, and following up with stakeholders to ensure data completeness and accuracy
• Strong attention to detail
• Demonstrated organizational and time management skills
• Effective communication and interpersonal skills
• Ability to work collaboratively in multidisciplinary teams
• Self-driven, proactive, and adaptable
• Ability to work independently and take initiative
• Working knowledge of statistical software (e.g., R, STATA, or Python) is an added advantage

• Bachelor’s degree in Statistics, Data Science, Actuarial Science, Public Health, or a related quantitative discipline.