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 NYPD strives to foster a safe and fair city by incorporating Neighborhood Policing into all facets of Department operations and solve the problems that create crime and disorder through an interdependent relationship between the people and its police and by pioneering strategic innovation.
The Office of Management Analysis and Planning (OMAP) analyze 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 Research 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. A successful candidate will contribute to the section mission by designing and developing technology solutions that solve department challenges. They also will harmonize analysis and research to advise leadership on policy and improve department decision making. Key responsibilities include experience with python and machine learning the ability to work with both structured and unstructured datasets (e.g. text geospatial network data) and the ability to write clean code to integrate data solutions with business intelligence tools. Strong project management and relationship skills are required. WORK LOCATIONQualifications :
1. For Assignment Level I (only physical biological and environmental sciences and public health) A masters 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; or
2. A masters 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; or
3. Education and/or experience which is equivalent to 1 or 2 above. However all candidates must have at least a masters 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.
Additional Information :
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 individuals sex race color ethnicity national origin age religion disability sexual orientation veteran status gender identity or pregnancy.
Remote Work :
No
Employment Type :
Full-time
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