The Center for Open Science (COS) is undertaking a project (to be announced) to automate and validate methods for assessing credibility of research claims in the social-behavioral sciences. COS will (1) create a large, enriched dataset of claims and evidence, (2) advance the efficiency and scalability of gathering that data, and (3) conduct replications and reproductions of a sample of the claims to test the accuracy of confidence scores generated by partners. The project is expected to run from January 2019 to December 2021.
The Data Scientist will evaluate project effort and accuracy, lead meta-analytic analysis across replication outcomes, lead evaluation of accuracy by partner labs in predicting replication outcomes, and complete monthly reports on the qualities and characteristics
of the enhanced dataset. The Data Scientist will also provide consulting support to the Project Managers and the network of partner labs in design and analysis planning. Finally, the Data Scientist will conduct statistical review of completed study plans.
The Data Scientist will report to the Program Manager and support both replications and dataset enhancement efforts.
- Statistical planning and review for a wide variety of statistical methods in the social-behavioral sciences
- Fostering reproducible workflows
- Data analysis of a large enhanced dataset of research claims
- Continual written reports on the research process and qualities of the collected data
- Meta-analytic efforts across replication projects
- Statistical consulting with the network of collaborating research teams
- Collaboration with the Data Manager to aggregate replication/reproduction efforts to create a large, enriched dataset of claims and evidence
- Supporting the statistical and methodological rigor of the overall project objectives
- Strong documentation practices for all project activities, including code and process, to ensure transparency and reproducibility
- Expertise (PhD or equivalent) in computationally oriented research domain; experience in one or more social-behavioral science disciplines preferred
- Very strong research methodology and statistical competencies that are transferable across a variety of research applications
- Experience manipulating data through statistical software (e.g. R)
- Demonstrated commitment to transparency, rigor, and reproducibility in research
- Expertise with R and reproducible workflows
- Experience with OSF, preregistration, replications (new data testing same question) and reproductions (reanalysis of same data) preferred
- Highly efficient and task-oriented
- Attention to detail and very strong documentation and workflow management skills
- Excellent written and oral communication skills, interpersonal skills, and ability to work independently and in coordination with a team for advancing shared objectives on a very assertive timeline
- Ability to prioritize, make decisions, problem-solve, and ask for help
This position is located at the Center for Open Science in Charlottesville, VA. On-site is highly desired, but remote work will be considered. Start date of early 2019 is unlikely to be flexible. However, COS will not require that senior graduate student applicants have defended their PhD by the start date. This is a full-time exempt position. Salary is expected to be ~mid-$80s.
COS offers full time employees:
401(k) with employer match. COS offers a matching contribution of 100% up to 3% of pay and another 50% up to 5% of pay (the full match will be 4% if participants elect to defer 5%).
Health, dental, and vision insurance. COS covers 100% of employee premium and 50% of all dependent coverage costs under the base plan
15 days of paid time off in year one
Paid family medical leave. COS offers paid leave for up to three (3) months to all full-time, regular employees to care for their child after birth, after or during the adoption process, or to care for their spouse, child, or parent who has a serious health condition.
Modern office space and other amenities.
Please submit a resume/CV and cover letter explaining your background and interest in the position. Two or more letters of recommendation can be submitted to email@example.com by the recommendation writer in support of the application. Letters should provide insight on the candidate’s possession of competencies listed above and capacity to meet the described responsibilities. Please instruct letter writers to include the candidate’s name in the subject line of the email. Questions about the position and COS are welcome and can be directed to firstname.lastname@example.org. COS is an equal opportunity employer and strongly encourages applications from members of groups underrepresented in science and technology industries.