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About the Job
Taimaka, as an organization, cares deeply about maximizing our cost-effectiveness. For instance, we shut down our initial program, a post-harvest loans initiative on which the organization was founded, when we ran an RCT and determined that it was insufficiently cost-effective.
We believe our current work is highly cost-effective, saving a life for every ~$1.6k-$1.7k spent, based on combining our cost and program performance data with GiveWell’s cost-effectiveness modeling for acute malnutrition. However, there are large error bars around that underlying modeling, due in part because of a lack of direct comparison data illuminating the mortality rates of treated vs. untreated children with severe acute malnutrition.
Taimaka is working with a large, well-known Effective Altruist charity evaluator to collect better data on acute malnutrition treatment programs to try to reduce uncertainty around its estimates of the cost-effectiveness of acute malnutrition. If we are successful in reducing these error bars, and acute malnutrition treatment remains highly cost-effective, this project could lead to that evaluator moving tens or hundreds of millions of additional dollars annually into acute malnutrition treatment.
To implement this project, we are hiring two Field Research Associates on our “CMAM Evaluation” team. As on of these Field Research Associates, you will run a portion of our cost-effectiveness research portfolio, which includes:
- A study of treated children over a 12-month follow-up period with a set of matched, healthy community controls to assess the mortality rate of treated malnourished and healthy children, as well as the relapse rate of treated malnourished children.
- Bi-annual surveys of prevalence, coverage, and mortality rates in the catchment areas served by 6-12 of our outpatient facilities.
- Year-round assessment of what percentage of children we are treating actually live in our designated catchment areas vs. commute to our facilities from outside of those areas.
- Working with other NGOs who implement in areas without functioning malnutrition treatment referral networks to collect data on mortality and anthropometric status.
In addition, you will conduct desk research to support work on similar priorities, like identifying existing data sources or published literature that may be able to provide points of triangulation around untreated mortality. You will be expected to become familiar with thinking about and modeling cost-effectiveness in the Effective Altruist style.
You will be guided in your work by Taimaka’s director of Research and Program Improvement. In addition, an experienced consultant will help in the set-up of the prevalence, coverage, and mortality assessments in 2025. You will, in turn, oversee teams of field data collectors, as well as one to two mid-level managers to assist in running those teams.
We view this role as fitting into the later half of someone’s early career. Our priority is finding candidates who can work entrepreneurially – identifying key problems, work independently, and self-start – and think for themselves. We’re looking for scrappy innovators, so if you think you fit that, please apply even if you have to do some learning on the job.
Specific Responsibilities
Your specific responsibilities may change depending on which elements of our cost-effectiveness research portfolio you end up working on, as well as evolve over time as our plans develop during 2025, but generally we expect your day to day to fall into a couple of key buckets:
Planning Data Collection Efforts
- Plan implementation methods and timelines for specific research projects. Draw on existing guidelines and field toolkits, upskilling yourself where needed.
- Write protocols, draft guidance documents, develop training materials, prepare budgets, and guide procurements of equipment and commodities for assigned projects, to align with methods and timelines.
- Map program catchment areas and construct population estimates to facilitate sample selection for surveys of prevalence and coverage with the support of an experienced consultant.
- Design and supervise the translation of survey questionnaires.
- Develop data collection tools (Open Data Kit forms, paper forms, etc.) and supervision checklists for data collectors and managers to use in implementing research projects. Implement orientation and training for teams of data collectors and data collection supervisors on SMART methodology or similar, with the support of an experienced consultant.
- Oversee community awareness and sensitisation for assigned research projects, including meeting with community leaders to introduce new projects, sharing updates with relevant contacts, and working with our community mobilisation team to address key tensions as they arise.
- Project-manage implementation of assigned research projects.
Monitoring Data Quality
- Conduct weekly data monitoring efforts with the supervisors or program officers you manage to assess fidelity of implementation of protocols and check for poor quality submissions from your field teams.
- Write code in R or Python to automatically pull data, clean it, and flag potential problem areas, including by cross-checking research/survey data and CMAM program data. Train and support program officers to regularly review and interpret this data.
- Design and implement a feedback loop to ensure that poor quality submissions and potential problems are documented, investigated and addressed.
- If you identify sources of poor quality data, take immediate corrective action, including form changes, retraining, or replacement of personnel.
- Design and implement processes for data verification and triangulation, including back checks, quality audits, and qualitative data collection (interviews, focus groups) to proactively identify and address data issues.
People Management
- Write job descriptions, advertise new roles, develop test tasks, and assess applications to hire new field data collectors and supervisors to support your assigned projects.
- Provide day-to-day oversight of your team, conduct performance reviews, provide training, and support team members’ professional development.
- Coordinate with the core CMAM program delivery team to ensure that routine data collection meets the needs of assigned research projects and troubleshoot coordination and quality issues related to program data collected by inpatient and outpatient staff.
- Meet regularly with the research management team to discuss progress and challenges.
Desk Research, Modeling, and Translating Your Learnings into Program Action
- Conduct literature reviews and other similar research efforts into related areas, like untreated acute malnutrition mortality rates, to support our cost-effectiveness modeling.
- Assist in re-working and improving sections of our cost-effectiveness model.
- Clean and analyse data collected for assigned research projects, including calculating key indicators according to established standards (i.e., death rate, GAM prevalence), conducting exploratory data analysis, and calculating inputs for cost-effectiveness modelling.
- Develop informative, concise reporting of your assigned research projects for internal and external audiences.
- Where your research identifies ways to improve our programming (e.g., creating a better understanding of the relationship between prevalence/coverage and case severity at admission), draw up guidelines to be incorporated into the treatment program.
Future Growth Trajectories
- This cost-effectiveness modeling effort is a three year project that may expand based on how successful it is. If you excel in this role and we expand this project, you could lead larger, cutting-edge research projects designed to identify the core drivers of how lives are saved via acute malnutrition treatment, like figuring out how to directly compare treated and untreated mortality or leading research into improved triaging methods to target treatment to patients who will not recover on their own.
- Depending on your interests, you could also focus more in this job on specializing in cost-effectiveness modeling. Alternatively, if you are more interested in the field side, you could specialize in running field trials, and work for Taimaka or another implementer on improving our protocols and practices.
About You
- This role will likely suit an early to mid-career public health (or similar) specialist with an interest in research. Our preference is for someone with a few years of work experience under their belt, but we may make exceptions for truly exceptional candidates.
- If you are not sure whether you’re the right fit for the position, err on the side of applying. Our initial application is designed to be fairly painless to complete and our priority is finding candidates with high overall potential, an ability to learn, and who align with our core philosophy of cost-effectiveness and innovation, rather than who check specific boxes.
Must Haves:
Candidates must have the following to qualify:
- Bachelor’s degree or higher in public health, statistics, economics, or similar
- Past experience with data analysis in either R OR Python Pandas
- An ability to learn new skills, particularly by diving in headfirst and learning by doing
- An ability to set your own priorities and independently solve problems
Nice to Haves:
The more of these that describe you, the better, but none are required. Even if none of these describe you, but you feel like you are talented and can learn, err on the side of applying.
Past experience with:
- Technical:
- An XLSForm based data collection platform (e.g., Open Data Kit, KoboCollect, SurveyCTO)
- Geospatial data collection and mapping using ArcGIS, QGIS or similar software
- General:
- Field experience in an LMIC, particularly if you were doing work related to data collection
- Experience or training implementing SMART or similar surveys related to child nutrition and mortality
- Familiarity with GiveWell/Effective Altruist methods of evaluating cost-effectiveness
- A Master’s degree in public health, statistics, economics, or similar
- 1 year or more of work experience in field research