Statistician / Data Scientist – Philippines
QED.ai (https://qed.ai) is a tech company focused on public health and food security in Sub-Saharan Africa. We build the digital infrastructure and artificial intelligence that empowers the intersection of aid and scientific inquiry, including epidemiological surveillance of HIV and malaria, and in-situ nutrient analysis of crops and soils using spectroscopy and computer vision. Our funding comes from philanthropic and governmental organizations such as the Global Fund, CDC, and the Gates Foundation.
We are looking for a Statistician and Data Scientist based in the Philippines to join our team.
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:
Analysis of data quality, including timeliness, completeness, and correctness.
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 sociodemographic disaggregations.
Statistical analysis of spectroscopic data related to agronomy (e.g. crops and soils), environmental health monitoring, food quality control, and other applications.
Construct dashboards to present and visualize data analytics, implemented using SQL and git version control.
Collaborate with governmental, medical, agronomic, and computer science teams in the composition of research papers and impact reports.
Requirements
Technical
Proficiency with core ideas in statistics.
Ability to use computer programming to wrangle, inspect, and analyze statistical data.
Formal academic studies in statistics, data science, or software engineering, coupled with some practical experience with analyzing real-world datasets.
Practical proficiency in analyzing real-world datasets with traditional statistical techniques, such as regression, hypothesis testing, 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 and Python-based programming environments.
Curiosity, tenacity, and creativity.
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 Kaggle data science competitions, the Philippine Mathematical Olympiad, or the Philippine National Olympiad in Informatics.
Experience with medical data, epidemiology, or agricultural data.
Domain knowledge and/or interest in the sustainable development goals, particularly public health,agriculture, climate change, and/or assisting developing countries.
Strong candidates can be invited to physically relocate long-term to our sites in Sub-Saharan Africa to be immersed with public health officers and data analysts working on the sustainable development goals.