Visiting Scientist, Bibliometrics and Science of Science

Schmidt Sciences • New York, NY

2d • Onsite

About The Position

The Science Systems Center at Schmidt Sciences is hiring a 12-month Visiting Scientist focused on bibliometrics and the science of science. The role combines improving how the organization assesses program outcomes with helping shape its approach to scholarly infrastructure and the scientific record as AI changes how research is produced, published, discovered, and verified. Early-career researchers and mid-career or senior researchers on sabbatical will be considered. Start dates are flexible.

Reporting to the Director of the Science Systems Center, the Visiting Scientist will work with the Science Systems team. Responsibilities will be developed jointly with the individual and manager and may change over time. Approximately 80% of the role will focus on portfolio impact and strategy, including reviewing and improving program outcome assessment, developing approaches to track awardee and program outcomes, creating analyses and tools using AI and large-scale bibliometric data, and assessing and advising on scholarly infrastructure investments. Approximately 20% will be dedicated to an independent research agenda in bibliometrics and the science of science, using publicly available or independently obtained data.

The position is based on-site in New York and requires regular travel within the U.S. and internationally as needed. This is an exempt position. Schmidt Sciences is an equal opportunity employer and prohibits harassment.

Requirements

• PhD or equivalent from an accredited university in information science, computer science, applied mathematics, statistics, or a related field relevant to the science of science.
• At least 2 years of postdoctoral or equivalent professional experience in academia, industry, government, or private research organizations.
• Demonstrated expertise in bibliometrics, scientometrics, or the science of science, evidenced by peer-reviewed publications or comparable contributions.
• Hands-on experience working with large-scale data on publications, citations, researchers, and collaboration networks.
• Demonstrated effective use of AI in research and data analysis.
• Experience building databases, analytical tools, or software for science of science analysis.
• Ability to translate research into practical recommendations for program teams and non-specialist audiences.
• Proven ability to operate autonomously, make informed decisions, and work with interdisciplinary teams.
• Must be based on-site in New York and able to travel regularly within the U.S. and internationally as needed.

Nice To Haves

• Experience designing or conducting program evaluation or research assessment, particularly for funders, universities, or research organizations.
• Expertise in measuring interdisciplinary research or tracking researcher career outcomes.
• Familiarity with scholarly communication and research infrastructure, including open scholarly data, preprints, and the integrity of the scientific record.
• Experience with strategy development, landscape analysis, or program design.
• Experience building analytical tools for non-technical users.

Responsibilities

• Review how programs across the Center collect, review, and assess outcomes, and recommend improvements.
• Design and pilot practical approaches to track awardee and program outcomes over time, including measures of interdisciplinary research.
• Develop analyses and tools that program teams can use directly, making effective use of AI and large-scale bibliometric data.
• Assess the Center’s current investments in strengthening the scientific literature and map efforts related to scholarly infrastructure and the scientific record, including the effects of AI on publishing, discovery, and verification.
• Help shape the Center’s future strategy for scholarly infrastructure and the scientific record, including recommendations on potential investments and program directions.
• Pursue an independent research agenda in bibliometrics and the science of science using publicly available or independently obtained data.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree