Senior Data Scientist

The mission of the New York City Police Department is to enhance the quality of life in New York City by working in partnership with the community to enforce the law, preserve peace, protect the people, reduce fear, and maintain order. The New York City Police Department strives to foster a safe and fair City through the strategic deployment of resources, focusing on both crime prevention and addressing quality‑of‑life concerns while building lasting community relationships.

The Office of Management Analysis and Planning (OMAP) analyzes and evaluates Departmental policies, programs, and resources to make recommendations to the Police Commissioner in order to ensure maximum organizational efficiency and effectiveness of the Department. OMAP is the research and assessment arm of the Department, comprised of both uniformed and civilian members of the service with a wide variety of academic and professional experiences.

OMAP conducts analyses aimed at improving the effectiveness and efficiency of the Department (e.g., personnel deployments, resource allocation), develops complex pilot projects, formulates policy recommendations and prepares briefing materials for the Police Commissioner on a wide range of legislative and procedural issues.

The Office of Management Analysis and Planning (OMAP) is seeking a skilled and highly motivated Senior Data Scientist to join the New York City Police Department (NYPD) Data Science team. OMAP serves as the primary evaluation and assessment arm of the NYPD. Acting as a "think tank," OMAP focuses on exploring and implementing innovative strategies and efficiencies aimed at enhancing policy development, evaluating programs, and optimizing organizational structures and staffing.

• Provide technical leadership and design data science services that solve Department challenges.
• Harmonize software across data science projects and deliver advanced machine learning solutions.
• Expert‑level development work in Python, wrangling both structured and unstructured datasets (e.g., text, geospatial, network data), and designing effective software architecture.
• Lead and manage projects, demonstrating strong project management and team‑building skills.

Minimum Qualifications

1. For Assignment Level I (only physical, biological and environmental sciences and public health) A master's degree from an accredited college or university with a specialization in an appropriate field of physical, biological or environmental science or in public health.

To be appointed to Assignment Level II and above, candidates must have:

• 1. A doctorate degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and one year of full-time experience in a responsible supervisory, administrative or research capacity in the appropriate field of specialization.
• 2. A master's degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and three years of responsible full-time research experience in the appropriate field of specialization.
• 3. Education and/or experience which is equivalent to "1" or "2" above.

However, all candidates must have at least a master's degree in an appropriate field of specialization and at least two years of experience described in "2" above. Two years as a City Research Scientist Level I can be substituted for the experience required in "1" and "2" above.

Note:

Probationary Period. Appointments to this position are subject to a minimum probationary period of one year.

• Ability to lead code reviews for the data science team and maintain core software packages.
• Experience designing full‑stack software products using Python, SOL, and/or R.
• Experience designing statistical and machine learning models (e.g., scikit-leam, stats models, PyTorch, Hugging Face).
• Experience performing a wide range of data science tasks, including but not limited to data visualization, natural language processing, geospatial analytics, and network analysis (e.g., Pandas, Num Py, Matplotlib, NL TK, Geo Pandas,…