Lead Data Scientist, Justice Processes
City of New York
ABOUT THE OFFICE:
The Mayor’s Office of Criminal Justice (MOCJ) advises the Mayor of the City of New York on criminal justice policy. MOCJ develops and implements strategies, with partners inside and outside government, to reduce crime and incarceration and to promote fairness and legitimacy. MOCJ works with law enforcement, city agencies, non-profits, foundations, and others to implement data-driven strategies that address current crime conditions, prevent offending, and build the strong neighborhoods that ensure enduring safety.
The Research Innovation Policy team drives the development and effective implementation of precision public health and public safety initiatives. Drawing on evidence-based and community-based insights, the Research Innovation operates through four main pillars: data-driven policy development, evaluation, quality assurance, and interagency coordination.
ABOUT THE ROLE:
Reporting into the Executive Director of Research Innovation, and as part of the Policy Unit, the Lead Data Scientist for Justice Processes is responsible for designing, testing, and communicating data-driven policy solutions to improve justice process efficiency, flow through the system and problem-solving off-ramps, and safely reduce the jail population. This involves both leveraging existing evidence-based insights to drive policy and crafting a data science-driven research agenda that supports the resolution of the most pressing issues. It will also involve incorporating nuanced data-driven insights into trainings, curriculums, external messaging, and other high-impact contexts. The successful candidate must be able to develop and maintain relationships with research, program, agency, community, and justice-involved partners. They must be creative, highly motivated, and able to manage projects from inception through implementation.
The Lead Data Scientist on Justice Processes responsibilities include but are not limited to:
- Conduct exploratory data analysis and build descriptive and predictive models to support policy and practice.
- Design, build, and deploy machine learning models into production environments, including monitoring for model drift and performance degradation over time.
- Create reproducible workflows in Python, R, and SQL, and maintain well-documented research processes.
- Deliver policy briefs, presentations, and interactive dashboards that translate complex findings into actionable, decision-ready evidence.
- Partner with city agencies, nonprofits, and justice system stakeholders to scope projects and align research with operational needs.
- Support public and stakeholder engagement by presenting results at conferences, policy forums, and cross-agency working groups.
- Preparing insights for publication or for internal use only as appropriate.
**PLEASE INCLUDE YOUR RESUME AND COVER LETTER SPECIFIC TO THIS POSITION
RESEARCH PROJECTS COOR(MA)-MGR - 0527A
1. Do you have a baccalaureate degree from an accredited college or university?
2. Do you have an associate degree from an accredited college or university along with two (2) years of experience with administrative, analytic, coordinative, supervisory or liaison responsibilities?
3. Do you have a four-year high school diploma, or its educational equivalent approved by a state's Department of Education or a recognized accrediting organization along with four (4) years of experience as described in question "2" above?
4. Do you have a satisfactory combination of education and/or experience equivalent to that described in questions "1," "2," and/or "3" above?
The City of New York is an inclusive equal opportunity employer committed to recruiting and retaining a diverse workforce and providing a work environment that is free from discrimination and harassment based upon any legally protected status or protected characteristic, including but not limited to an individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, veteran status, gender identity, or pregnancy.