Job Title: Senior Associate, Innovation and Data Integration
Organisation: Evidence Action
Duty Station: Kampala, Uganda
About Organisation:
Evidence Action is an international non-profit organization that scales high-impact, low-cost health and development interventions backed by rigorous research. In Uganda, the organization plays a massive role in public health, primarily through clean water access initiatives that serve millions of people across rural and peri-urban communities.
Job Summary: You will oversee data systems and analytics for Evidence Action’s new In-Line Chlorination Innovation Team, under the Safe Water Now Program. Evidence Action’s Safe Water Now program provides access to safe drinking water across Kenya, Uganda, Malawi, and India through water chlorination. Backed by rigorous research showing chlorination can reduce child mortality by more than 20%, safe water is one of the most cost-effective health interventions globally.
The program’s newest intervention, In-Line Chlorination (ILC), automatically treats water as it flows through piped systems, requiring less behavior change from end users than existing solutions. As ILC scales up, core questions remain about how to optimize device performance, reduce operational costs, and strengthen community engagement. Answering these questions well will shape whether ILC can become a scalable, cost-effective model reaching millions more people. Evidence Action is investing in a dedicated Innovation team to find those answers.
This new team will conduct rapid field pilots testing improvements to the ILC model. Your job is to make sure those pilots produce data the team can trust and act on. You will design the data collection tools, build the dashboards, and own the pipeline from field measurement to operational decision. This is not a monitoring or evaluation role: the goal is to get useful information into the hands of field staff and program managers fast enough to change what happens next. Based in Mbale, Uganda, you will report to the Manager, Innovation & Learning, and work closely with both Field Technicians and the MLE Team.
Key Duties and Responsibilities:
- Data Collection Design and Quality: Design and oversee data collection processes that produce reliable field data across the Innovation team’s device portfolio
- Supervise a data collection team that conducts spotchecks of data collected by field technicians
- Build and iterate on survey instruments and collection protocols tailored to each pilot’s learning goals
- Train field technicians on data collection procedures and conduct regular quality checks
- Identify and troubleshoot data quality issues as they emerge, including measurement inconsistencies, protocol deviations, and instrument problems
- Support pilot design by helping define what to measure, how to measure it, and what thresholds would indicate success or failure
- Data Systems and Dashboards: Build and maintain the data pipeline from field collection through to usable outputs
- Design and manage operational dashboards from the ground up tracking device performance, dosing consistency, visit frequency, and other pilot-specific indicators
- Own the data cleaning and transformation process, working with MLE teams where appropriate
- Data-Driven Decision Support: Integrate data from dashboards you create into timely, actionable input for the team’s weekly planning and pilot decisions
- Embed data into weekly workplanning by producing clear signals on which devices need attention, which pilots are on track, and where adjustments are needed
- Support creation of decision processes across the program that directly utilize and integrate data effectively
- Analyze emerging pilot results and present findings to the team lead and field staff in accessible, non-technical terms
- Flag when data is insufficient or unreliable rather than forcing conclusions from weak evidence
- Data Quality and Integrity: You will be assessed on the accuracy and reliability of field data, including whether quality issues are caught early and resolved.
- This includes overseeing the performance of data collection officers
- Data System Delivery: You will be assessed on whether the Innovation team has functioning, reliable data infrastructure, including collection tools, dashboards, and a clean pipeline from field to decision.
- Speed matters: the time from field collection to usable analysis should be short enough to inform weekly decisions
- Data Integration into Decisions: You will be assessed on whether pilot data is consistently embedded into the team’s weekly planning and pilot design decisions, and whether the team finds the tools and outputs useful enough to actually rely on.
Qualifications, Skills and Experience:
- Bachelor’s degree in Statistics, Economics, Data Science, Public Health, or a related field.
- Possession of a post graduate qualification in M&E, Statistics, Data Science or related field will be added advantage
- 4+ years of experience in data management, program analytics, business intelligence, or applied research in a field-based setting.
- Candidates from a variety of backgrounds are welcome, including private sector
- Proficiency in statistical software (STATA, R, or similar) and experience building dashboards (Tableau, Power BI, or similar)
- Experience building data systems or processes from scratch, not just maintaining existing ones
- Strong communication skills including ability to present technical findings to non-technical audiences
- Comfort with ambiguity and rapid iteration
- Fluency in English; local language skills an advantage
- Willingness to be based in Mbale, Uganda with 50%+ field travel
Position Location
- This role will be based in Mbale, Uganda, with regular travel to field sites.
- We are unable to sponsor or take over sponsorship of Uganda employment visa at this time. Applicants must be legally authorized to work in Uganda for roles based in Uganda.
- Note: Applications will be reviewed on rolling basis.
How to Apply:
All suitably qualified and Interested applicants should apply online at the link below.
NB: Only shortlisted candidates will be contacted.
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Level of Education: bachelor degree
Work Hours: 8
Experience in Months: 48