Staff Associate II (Data Scientist)
The Department of Environmental Health Sciences at Columbia University Mailman School of Public Health seeks a Staff Associate II (Data Scientist) for work on infectious disease systems. The successful candidate will support multiple projects investigating infectious diseases, managing large data resources and systems, and supporting infectious disease research and operational forecasting. The data scientist will join a dynamic team of computational biologists, epidemiologists, and mathematicians researching a range of infectious diseases, including influenza, COVID-19, malaria, dengue and anti-microbial resistant organisms.
The successful candidate will:
- Conduct research including quantitative study of the environmental and social drivers of infectious disease transmission and outcomes, development of data-driven mathematical model-inference systems capable of accurately simulating and forecasting infectious disease incidence at the population level, and support study of the genetic underpinnings of infectious disease outcomes at the individual level. (50%)
- Contribute to project management and data support including database management, data and model output archiving and posting, and data processing. (25%)
- Develop written reports of findings and activities. (10%)
- Support the development of new research projects in collaboration with the larger scientific team. (10%)
- Perform related duties and responsibilities as assigned/requested. (5%)
- Bachelor’s degree in data science, computer science, statistics, or a related discipline.
- Experience programming in three or more of the following languages—Matlab, R, Python, JAVA, SQL, OpenGL, C++--is required.
- Strong technical and numerical skills, a love of research and inquiry, an ability to work both collaboratively and independently, and strong oral and written communication skills are also needed.
- A Master's degree in data science, statistics or a related field or two-years work experience is a plus.
- Persons with a strong background and interest in statistics, machine learning and data mining are encouraged to apply.
Last updated: Thursday, January 5, 2023 20:36 UTC