Applied Statistician - Public Health & Biostatistics
At a glance
Mid-level Data Science role at QED.ai. Global · full-time.
Pay not stated Data Science salary
dataroles summary, based on the employer's posting.
What you'll do
- Analyze national health data on HIV, TB and malaria, including treatment outcomes, testing patterns and survival
- Check health datasets for gaps, delays and errors, then turn findings into usable indicators
- Work with healthcare workers and epidemic intelligence officers to move urgent data findings into action
- Build SQL dashboards with git to show and explore statistical results
- Develop automated analyses and work with government, medical and computing teams on policies and research
What you bring
- Formal academic study in statistics, data science or AI, plus strong command of statistical fundamentals
- Practical experience applying traditional statistical methods to real-world data, such as regression, surveys or time series
- Strong SQL and R or Python skills, including data cleaning and analysis, with git version control
- Working English at C1 level or higher, in speech and reading, and clear written communication
Who this fits
This role suits a statistician interested in applying both conventional methods and newer AI techniques to public health data. You’ll work with government, medical and computing collaborators, and help guide field teams. The role strongly favors candidates willing to relocate long-term to sites in Sub-Saharan Africa; possible placements include Malawi, Côte d’Ivoire, Cameroon, Nigeria and Mozambique.
From the employer
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 amazing team. The statistician will combine traditional knowledge with the exciting and rapidly advancing world of AI. Strong preference will go to statisticians willing to be based in Sub-Saharan Africa. Possible countries of initial placement include Malawi, Cote d'Ivoire, Cameroon, Nigeria, and Mozambique.
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.
Automation is key, and AI will be in all aspects to build on top of our existing agentic platforms for automated analysis.
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
Formal academic studies in statistics and data science / AI.
High proficiency with core ideas in statistics.
Enthusiasm and strong interest in post-2022 AI. Experienced with latest AI-powered coding techniques and agn
Ideal: 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.
Publications in peer-reviewed journals related to biostats and public health.
Practical proficiency in analyzing real-world datasets with traditional statistics, such as regression, hypothesis testing, experimental and survey design, time series, and RCTs.
Non-trivial subject matter expertise in global health epidemics, such as in HIV, TB, malaria, and/or global health surveillance.
Proficient in cleaning, validating, and reconciling complex real-world datasets --- preferably medical or epidemiological in nature -- and working alongside domain experts.
Practical proficiency in analyzing real-world datasets with modern machine learning methods, such as decision trees, boosting, and neural networks.
Computer programming skills in wrangling, inspecting, and analyzing data statistically. High fluency in SQL and R/Python. 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, such as mathematics or informatics olympiads.
Fluency in French or Portuguese to assist with potential relocation to Francophone and Lusophone countries.
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