EcoHealth Alliance seeks a creative, self-motivated and technically adept Research Scientist to support projects in epidemiological modeling, forecasting, and new disease detection. The Research Scientist will work with our computational sciences team to develop and test both mechanistic and statistical models of disease outbreaks, develop a database of outbreak events and predictors, and build automation tools to gather data and publish model results. The Research Scientist will also collaborate with field and laboratory teams in developing workflows to support project data collection and analyses.

This position is based in New York City with a remote option. The candidate must be available to collaborate with team members via email, chat, and video calls during US EST business hours and to be available as needed to coordinate with collaborators in other time zones.

DESCRIPTION AND RESPONSIBILITIES:

Reporting to the Principal Scientist for Computational Research, the Research Scientist will:

Develop pipelines to collect and archive data from epidemiological and scientific sources

Build and fit mechanistic and statistical models of disease circulation

Develop methods to assess and compare epidemiological forecasts

Work collaboratively with a team via meetings, code reviews and provide feedback on team modeling outputs

Write and revise scientific publications

Support other teams and staff in data processing, analysis, and visualization tasks

Perform other tasks as assigned by supervisor

MINIMUM QUALIFICATIONS:

M.S. or Ph.D. in epidemiology, data science, statistics or related quantitative field. B.A. or B.S. candidates with a degree in these fields will be considered with 2+ years of relevant experience, and candidates without a degree will be considered with 4+ years relevant experience.

Strong R programming skills

Experience building and fitting mechanistic ecological or epidemiological models

Experience with predictive regression or machine-learning models

Demonstrated ability to self-teach and train others in new software tools and methods

Knowledge and experience some methods of reproducible research and automation: git, GitHub, SQL databases, Docker, web automation tools

 Ability to work collaboratively in teams with culturally- and technically-diverse backgrounds

Strong verbal and written communication skills

 Strong data management and project management skills, including ability to manage multiple projects and deadlines while working with multiple teams

OTHER PREFERRED QUALIFICATIONS:

Knowledge and experience working with genomic data

Knowledge and experience working with neural networks

Knowledge and experience developing model interfaces and dashboards with Shiny

Experience teaching and training teams in data management and data science software is a plus

Compensation will be $75,000 – $95,000 USD annually, commensurate with skills and experience.