Applied Statistician - Public Health & Biostatistics
QED.ai (https://qed.ai) is a technology and data analytics company focused on public health in Sub-Saharan Africa. We build the digital infrastructure and A.I. that empowers the intersection of aid and scientific inquiry, including epidemiological surveillance of HIV, malaria, and tuberculosis at national scale. Our funding comes from organizations such as the Global Fund, CDC, and the Gates Foundation.
We are looking for an Applied Statistician with experience in public health and biostatistics in to join our team and be based in Sub-Saharan Africa. The most likely initial placements are (1) Lilongwe, Malawi, and (2) Abidjan, Cote d'Ivoire.
Scope of Work
Statistical analysis of national-scale health data related to the control and elimination of epidemics such as HIV, TB, and malaria, including:
Construction and analysis of key epidemiological performance indicators, such as prevalence, testing and re-testing rates, adherence to testing protocols, retention and persistence on treatment, lab turnaround times, co-infection rates, survival rate analysis, and socio-demographic disaggregations.
Analysis of data quality, including timeliness, completeness, and correctness.
Co-direction of ground teams, including healthcare workers and epidemic intelligence officers, to urgently convert data into action --- and save lives.
Collaborate on a daily basis with governmental, medical, and computer science teams in the co-composition of impactful public policies, research papers and impact reports.
Construct dashboards to present and visualize data analytics, implemented using SQL and git version control.
Requirements
Technical
Willingness to physically relocate long-term to our sites in Sub-Saharan Africa to be immersed with public health officers, data analysts, and governmental chiefs that are working on the sustainable development goals.
Formal academic studies in statistics, data science, or software engineering.
High proficiency with core ideas in statistics.
Computer programming skills in wrangling, inspecting, and analyzing data statistically. High fluency in SQL and R/Python.
Proficient in cleaning, validating, and reconciling complex real-world datasets --- preferably medical or epidemiological in nature -- and working alongside domain experts.
Familiarity with public health, or a strong willingness to rapidly develop deep expertise in epidemic control through hands-on work and self-driven study.
Practical proficiency in analyzing real-world datasets with traditional statistics, such as regression, hypothesis testing, experimental and survey design, time series, and RCTs.
Practical proficiency in analyzing real-world datasets with modern machine learning methods, such as decision trees, boosting, and neural networks.
Proficiency with git version control.
Curiosity, tenacity, and creativity. Ability to work effectively through the many challenges and realities of international aid in the Global South.
General
Working proficiency (≥C1) in speaking and reading English, and capable of typing English with a speed of at least ≥45 words per minute.
Logical reasoning and ability to express oneself clearly, both orally and in writing.
Willingness and interest in working with people from other cultures. Emotional resilience and social intelligence to communicate and work with collaborators from around the world, including Europe, Africa, Asia, and the USA.
… and you have to care about the work that you do!
Bonus
Additional skills that are a bonus, but are not required:
Past participation in STEM-related national or international competitions.
Fluency in French, to assist with potential relocation to West African Francophone countries.