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 Manager will be responsible for creating, maintaining, and enhancing the large dataset of claims and evidence.
The Data Manager will work closely with the Data Enhancement partners to develop the dataset, manage claim extraction, merge data, and monitor automated and manual data coding and integration. The Data Manager will manage and document the dataset; liaise with external dataset managers to align their fields and process to move towards automated processing; manage grants for automated extraction and enhancement techniques; and support monthly reporting dataset and testing confidence scores contributed by other performing teams.
The Data Manager will report to the Program Manager, and will collaborate closely with the Data Enhancer and Claim Extraction Leads.
- Creating and curating a database of scholarly claims
- Maintaining and documenting that database for quality and wide use
- Enhancing the dataset with related data from a wide variety of scholarly databases using and developing automated techniques to keep the dataset up-to-date
- Enhancing the dataset with data extracted from papers and/or provided by other collaborators or performing teams-- Creating automated workflows for data extraction from sources
- Negotiating and collaborating with maintainers of other scholarly databases to align data for automated extraction and merging
- Maintaining overall data integrity for project success
- Maintaining permissions for data access
- Navigating licensing arrangements with external parties for use of proprietary data for integration with the enhanced dataset
- Expertise with data managing, data wrangling, data merging, and data documentation
- Expertise with scholarly databases and APIs
- Experience with programming skills for data extraction, merging, and creating automated, repeatable workflows with large databases (SQL experience is a plus)
- Practical understanding of and experience with machine learning a plus
- Demonstrated commitment to transparency, rigor, and reproducibility in research
- 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 graduate student applicants have defended their thesis by the start date. This is a full-time exempt position. Salary is expected to be in the mid-60s.
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. Questions about the position and COS are welcome and can be directed to email@example.com. COS is an equal opportunity employer and strongly encourages applications from members of groups underrepresented in science and technology industries.