Design and implement all aspects of a statistical consulting service to support quantitative research at the University. Improve the chances of faculty being awarded grants by support on grant proposals. Improve the quality of empirically-based research products by providing expertise and guidance in data collection, research design, and analysis. Create a state-of-the-art consulting environment for University faculty across a wide range of departments and centers.
This position will take a lead role in designing and launching a statistical consulting service to support quantitative research performed by faculty and researchers at the University. The successful candidate will develop methods and structures to understand and address the statistical support needs of faculty; design and implement a strategy for recruiting, triaging, and intaking potential projects; and contribute to planning to make the service sustainable within the larger strategic and technological frame of the University. This person will help in marketing the service to potential users, creating ongoing programming that further supports user communities in this area, and developing and teaching year-round statistical consulting seminars to help scaffold staff training, triage projects, and provide direct services.
This person will take a central role in developing and supervising a group of student staff specialists, including hiring, training, and evaluating them. This person will work to match student staff with incoming project proposals based on skill and breadth of project, and will ensure work quality, accuracy, and timeliness of the assigned student staff.
This person will work as a core member of the new Data Science and Software Services (DS3) unit, which seeks to provide fulsome services to faculty and researchers in utilizing data science and statistical methodologies in pursuit of their research goals. This innovative new service is a partnership between the NYU Center for Data Science (CDS), the NYU Libraries Data Services, and the Center for Practice and Research at the Intersection of Information, Society, and Methodology (PRIISM). The ideal candidate is someone who can work well within a highly collaborative environment, in close partnership with staff across these affiliated groups.
PhD in Statistics, Biostatistics, or related field
5 years' relevant experience or equivalent combination.
Broad statistical knowledge base, including but not limited to power analysis, classical techniques of hypothesis testing, multiple regression techniques of all types, multilevel modeling, and one or more of the following: GEE, SEM, or essential techniques of machine learning. Familiarity with Time Series, Survey, and Panel Data analyses.
Experience with collaborating or consulting with researchers involved in empirical research
Supervising student or other staff
Experience teaching and mentoring
Ability to analyze data in Python and/or R
Experience in an academic environment
Experience in applying for and managing externally-funded projects
Required Knowledge, Skills, and Abilities
Excellent leadership, interpersonal, organizational, analytical, problem-solving, and communication skills.
Facility with a wide-range of statistical software and programming languages.
Ability to train and provide technical advice to a non-technical audience.
For consideration, please submit your CV, statement/cover letter, and two references.
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