The Predictive Analyst will be a member of DOB’s Analytics & Data Science division that will work closely with the Enforcement Bureau to mitigate risk proactively and strategically with the overall goal of improving safety and quality of life in NYC. Specially, they will create and implement quantitative models to identify high-risk construction work for proactive audits and inspections.

Under direction, with wide latitude for independent initiative and judgment:
- Work closely with engineers to translate engineering criteria into queries, reports, dashboards, maps, etc.
- Evaluate methods, procedures, and data obtained from investigation and data mining
- Develop predictive modeling tools to support Agency initiatives
- Develop text mining analytics for various projects
- Assist with the management of predictive modeling tools and the development of tools to support technology integration and automation for the Agency
- Develop analytical tools for risk management, including Field Force Management analytics, bad actor, and anti-corruption analysis
- Develop automatic data cleaning tools
- Assist with the preparation of reports regarding the Agency’s use of predictive analytics and the effectiveness of proactive inspection programs
- Translate quantitative data, research findings, and insights into compelling and informative data visualizations
- Provide support, coordination, and implementation for various projects and programs
- Serve as a technical resource regarding utilizing predictive analytics to improve operations

Additional Information
Only permanent Administrative Staff Analysts, applicants who are reachable on the Administrative Staff Analyst open competitive list, and applicants as indicated below will be considered.

Candidates who are permanent in comparable civil service titles may be considered for title change under rule 6.1.9 of the Personnel Rules and Regulations of the City of New York

To Apply:

Visit Jobs NYC (cityjobs.nyc.gov) to view and apply for available positions. Search by agency (Department of Buildings), keywords, or for the specific Job ID #.

NOTE: ONLY THOSE CANDIDATES UNDER CONSIDERATION WILL BE CONTACTED.

1. A master's degree from an accredited college in economics, finance, accounting, business or public administration, human resources management, management science, operations research, organizational behavior, industrial psychology, statistics, personnel administration, labor relations, psychology, sociology, human resources development, political science, urban studies or a closely related field, and two years of satisfactory full-time professional experience in one or a combination of the following: working with the budget of a large public or private concern in budget administration, accounting, economic or financial administration, or fiscal or economic research; in management or methods analysis, operations research, organizational research or program evaluation; in personnel or public administration, recruitment, position classification, personnel relations, employee benefits, staff development, employment program planning/administration, labor market research, economic planning, social services program planning/evaluation, or fiscal management; or in a related area. 18 months of this experience must have been in an executive, managerial, administrative or supervisory capacity. Supervision must have included supervising staff performing professional work in the areas described above; or
2. A baccalaureate degree from an accredited college and four years of professional experience in the areas described in "1" above, including the 18 months of executive, managerial, administrative or supervisory experience, as described in "1" above.

- Sound understanding of statistical methods and solutions experience with industry standard Business Intelligence packages and tools such as RapidMiner, Oracle OBIEE, Tableau, Cognos, Business Objects, Python, R, SAS/Stata, or JavaScript - Understanding of risk models and statistical or social science methodologies and experience developing predictive models - Strong understanding of relational database structures, statistical reporting, data structures, algorithms, and technical analysis ability to manage and analyze large datasets - Knowledge of GIS and mapping tools - Ability to work independently and collaboratively - Knowledge of Microsoft Office programs such as Word, Excel, Access, Visio, Project, and PowerPoint ability to understand transactional data and manipulate data using Excel - Strong communication skills – written and verbal – and the ability to explain technical requirements in lay terms - Excellent organizational, presentation, and facilitation skills including the ability convey findings, statistics, and trends to non-technical audiences - Ability to handle multiple tasks simultaneously under tight deadlines

This position is also open to qualified persons with a disability who are eligible for the 55-a Program. Please indicate at the top of your resume and cover letter that you would like to be considered for the position through the 55-a Program.

As a prospective employee of the City of New York, you may be eligible for federal loan forgiveness programs and state repayment assistance programs. For more information, please visit the U.S. Department of Education’s website at https://studentaid.gov/pslf/.

New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.

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.