Description
The NYU Furman Center seeks a Data Management Associate with strong data management and organizational skills to support the ambitious and diverse data work occurring across the Furman Center. The Associate will be a member of the data team, which is responsible for cleaning, organizing, maintaining, and sharing data that is relevant to the work and mission of the NYU Furman Center. In addition to daily operations and administrative tasks, this work includes responding to data requests from a wide range of stakeholders, including: the research community; media; elected officials; policymakers; and government agencies. The successful applicant will be an entrepreneurial, collaborative, solutions-oriented, and mission-driven individual who is as comfortable with cleaning, organizing, and maintaining data as they are creating technical documentation and navigating data agreements with private and government partners.
The Data Management Associate will report directly to the Furman Center Data Manager and will work with a dynamic and interdisciplinary team of lawyers, economists, urban planners, and policy and data analysts. They will help develop and maintain high-quality datasets and technical toolkits that will preserve and curate the Center’s institutional knowledge about a wide range of data sets about housing, zoning, real estate, health, education, and other urban policy focused issues.
Key responsibilities include:
- Participate in a range of data management activities, including:
- Assemble, update, and maintain datasets that support research projects related to housing, land use, and neighborhood conditions.
- Build tools to organize guides, documentation, and code at the NYU Furman Center and its Housing Solutions Lab.
- Assist researchers with research tasks, including responding to technical questions and needs.
- Work with NYU Furman Center staff and affiliates to develop and improve the data products produced by the Furman Center and its Housing Solutions Lab, prioritizing responsiveness and usefulness for a variety of audiences.
- Work with project teams to draft data and code documentation, as well as guides that maintain institutional knowledge.
- Under the guidance of the Data Manager, assist with updates to flagship NYU Furman Center web-based tools, such as the State of New York City’s Housing and Neighborhoods, the Center’s annual neighborhood indicators report, and CoreData.nyc, a map of affordable housing developments in New York City.
- Manage both new and existing data use agreements, data storage security plans, and NYU Furman Center data products (for example, CoreData.nyc) with external vendors.
- Support the development of graduate student researchers and data-focused undergraduate office assistants with training, close collaboration, and supervision.
Minimum Qualifications:
A bachelor’s degree in policy, urban studies, statistics, or a related field, with at least one year of quantitative analysis experience and/or administrative experience (including research assistantship and internship). The ideal candidate will have a strong interest in ground-level data work, such as manual data cleaning, as a pathway to understanding cities, housing, and land use. The candidate should have basic work knowledge of R (Tidyverse).
The ideal candidate will have the ability to multitask, respond to shifting priorities, and meet strict deadlines. They will be comfortable working both independently and collaboratively and have a willingness to take initiative, coupled with strong organizational skills and attention to detail.
Preferred Qualifications:
An advanced degree in public policy/administration, urban planning, economics, applied statistics, data science, or a related field. Familiarity with administrative data, especially land use and housing data sets. Additional technical experience in relational databases (SQL, AWS-RDS), geospatial data management and analysis (R, Python, QGIS, ArcGIS, PostGIS), or version control and collaboration with Git/GitHub. Knowledge about data ethics is a plus.
Benefits and Terms of Employment:
The position comes with a salary and a generous array of benefits, which include medical, dental, and vision. Further information regarding benefits can be found at: https://www.nyu.edu/employees/benefit/full-time/professional-research-staff.html.
In compliance with NYC's Pay Transparency Act, the annual base salary range for this position is $55,000 - $80,000. New York University considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as market and organizational considerations when extending an offer.
The NYU Furman Center currently follows a hybrid schedule, with three days per week required in our New York City office. This position is expected to start spring/early summer 2023.
To Apply:
Applicants should submit a cover letter, resume/CV, writing and/or data visualization sample, names and contact information of three references, and salary requirements. Send application materials and questions to furmanjobs@nyu.edu. Please include “Data Management Associate” in the subject line. Review of applications will begin immediately. Only candidates selected for an interview will be contacted.
NYU is an Equal Opportunity Employer and is committed to a policy of equal treatment and opportunity in every aspect of its recruitment and hiring process without regard to age, alienage, caregiver status, childbirth, citizenship status, color, creed, disability, domestic violence victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic characteristics, pregnancy, race, religion, sex, sexual orientation, unemployment status, veteran status, or any other legally protected basis. Women, racial and ethnic minorities, persons of minority sexual orientation or gender identity, individuals with disabilities, and veterans are encouraged to apply for vacant positions at all levels.