rOpenSci - Software Research Scientist

NYC, Berkeley, Remote // Full Time

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rOpenSci - Software Research Scientist

Are you passionate about statistical methods and software? If so we would love for you to join our team to dig deep into the world of statistical software packages. You’ll develop standards for evaluating and reviewing statistical tools, publish, and work closely with an international team of experts to set up a new software review system.

We are seeking a creative, dedicated, and collaborative software research scientist to support a two-year project in launching a new software peer-review initiative. The software research scientist will work on the Sloan Foundation supported rOpenSci project, with rOpenSci staff and a statistical methods editorial board. They will research and develop standards and review guidelines for statistical software, publish findings, and develop R software to test packages against those standards. The software research scientist will work with staff and the board to collaborate broadly with the statistical and software communities to gather input, refine and promote the standards, and recruit editors and peer reviewers. The candidate must be self-motivated, proactive, collaborative and comfortable working openly and reproducibly with a broad online community.


· Research standards and protocols for evaluating statistical software quality and correctness, and the extent of their adoption
· Create new testing frameworks for R packages
· Assist rOpenSci staff and project board members in drafting new peer-review evaluation standards, guidelines, and documentation
· Write technical and scientific papers, documentation and blog posts
· Assist in organizing peer-review system for scientific software and managing the review board
· Participate in and represent the rOpenSci project in person and via on-line fora
· Participate in other projects and tasks as required or assigned by supervisor

Minimum Qualifications

· A Master's degree in statistics, computer science, or a related field with a focus on quantitative methodologies, or equivalent experience in statistical methods evaluation and development
· Expertise in open-source R package development, including collaborative development using Git and GitHub, testing frameworks, and continuous integration
· Strong writing skills
· Experience in collaborative team projects and consensus building
· A passion for improving scientific reproducibility

Desired Qualifications

· A Ph.D. in statistics, computer science, or a related field with a focus on quantitative methodologies, or equivalent experience in statistical methods evaluation and development
· Published scientific or technical articles or software documentation

The position will be based at EcoHealth Alliance in New York City. Flexible work arrangements may be made for uniquely qualified candidates. EcoHealth Alliance is an equal opportunity employer and we encourage people with a diverse range of backgrounds to apply. We offer comprehensive benefit package including health, dental, and vision coverage, and a 403(b) pension plan. For further information about EcoHealth Alliance, please visit our website:

HOW TO APPLY: Send an email a single attachment labeled with your first and last name only

(“first_last.pdf”) in PDF format containing with (a) a cover letter, (b) CV, and (c) contact information for three references to with "EHA 2019 ROPENSCI RESEARCH SCIENTIST" in the subject line. Applicants should include links to code repositories, online portfolios, and other demonstrations of experience. Links to contributions to open-source projects (documentation, pull requests, online discussions) are encouraged.

Emails without the subject line or with multiple attachments will not be received. No formal text is required within the body of your email, since only the attached document will be retained and reviewed by the hiring committee. All inquiries will receive an automatic response confirming receipt. Applications will be evaluated and only appropriate candidates will be contacted.


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