Property Tax Data And Policy Analyst

The NYC Department of Finance (DOF) is responsible for administering the tax revenue laws of the city fairly, efficiently, and transparently to instill public confidence and encourage compliance while providing exceptional customer service.

The Treasury and Payment Services Division is responsible for overseeing all City payment websites, the payment processing of tax returns, property recording forms, parking violation programs, and the collection of delinquent accounts, and oversees the agency's management of the City's cash balances and its relationships with banking institutions. Treasury and Payment Services is also responsible for collecting outstanding violations issued by City agencies and adjudicated by the Environmental Control Board.

Payments, Billing, and Refunds is responsible for processing payments for property taxes and property-related charges, business and excise taxes, and parking and camera violations. The division is responsible for communicating amounts due, maintaining the quality of departmental records, and providing customer service to individuals seeking information on making payments or receiving refunds. Payments, Billing, and Refunds performs account adjustments and responds to refund inquiries from the public.

The division seeks a thoughtful, dynamic, and motivated Property Tax Data and Policy Analyst. This role will be responsible for laying out the high-level architecture to build out the PTO Business Database, and then enable business dashboards and reports. The Property Tax Data and Policy Analyst will assist senior staff to reinforce a cultural shift amongst operations staff to make all business decisions through the use of data analytics.

Key responsibilities include:

• Manage and maintain consolidated database of Property Tax data.

• Research, compile, investigate and analyze large quantities of PT data from a variety of sources, with an eye to identifying cost saving opportunities and policy and operational implications.

• Recommend and implement improvements to Property Tax operations.

• Support automated data update processes and reports and develop automation for manual PT processes.

• Work closely with business owners and product managers to build and maintain ongoing analysis of their specific operational data processes, usage patterns and performance.

• Write database queries and code to analyze PTO service usage volumes, user behaviors and performance data to identify opportunities to gain operational efficiencies.

• Create and maintain dashboards for multiple users to view PTO trends and reports.

• Use database tools and spreadsheets to analyze data for the purpose of identifying patterns and supporting DOF analytics and reporting needs.

• Monitor integrity of data maintained in City's property tax system database, PTS, and ensure system meets ability to robustly sustain core business requirements.

• Evaluate data pertaining to property taxes and perform data analyses, where necessary, to improve the efficiency of operations.

• Develop GIS and geospatial visualizations to enhance interpretations and understanding of findings.

• Perform ad hoc database queries and analyze property tax payment plan applications and debt.

• Conduct in-depth data analysis to identify trends and provide solutions to issues related to property tax payment plans administration and tax collection as well as other Property Tax Payment Plan Operation issues.

Minimum Qualifications

Level I

1.A master's degree from an accredited college or university in social science, economics, statistics, computer science, data analysis, geography, sciences, technology, engineering, mathematics (STEM), or a closely related field, with at least 12 credits or five courses in economics, public policy, econometrics, statistics, mathematics, engineering, geography or computer science.

2.A baccalaureate degree from an accredited college or university as described in "1" above and two years of full-time, professional experience performing statistical analysis and programming work in any of the areas described in "1" above.

Level II

1.A master's degree from an accredited college or university in social science, economics, statistics, computer science, data analysis, geography, sciences, technology, engineering, mathematics (STEM), or a closely related field, with at least 12 credits or five courses in economics, public policy, econometrics, statistics, mathematics, engineering, geography or computer science.

2.A baccalaureate degree from an accredited college or university as described in "1" above and two years of full-time, professional experience performing statistical analysis and programming work in any of the areas described in "1" above.

Special Note:

To be eligible for placement in Assignment Level II, individuals must have, in addition to meeting the minimum requirements, at least one year full-time work experience in a related field, or a master's degree from an accredited college or university, in the areas described in "1" above, with at least 12 credits or three advanced courses in economics, public policy, econometrics, statistics, mathematics, engineering, geography, or computer science."

Level III

1.A master's degree from an accredited college or university in social science, economics, statistics, computer science, data analysis, geography, sciences, technology, engineering, mathematics (STEM), or a closely related field, with at least 12 credits or five courses in economics, public policy, econometrics, statistics, mathematics, engineering, geography or computer science.

2.A baccalaureate degree from an accredited college or university as described in "1" above and two years of full-time, professional experience performing statistical analysis and programming work in any of the areas described in "1" above.

Special Note:

To be eligible for placement in Assignment Level III, individuals must have, in addition to meeting the minimum requirements of Level II, at least three years full-time work experience in a related field, or a Doctorate degree from an accredited college or university, in the areas described above, with at least 12 credits or three advanced courses in economics, public policy, econometrics, statistics, mathematics, engineering, geography or computer science.

Preferred Skills

• Superior analytical and organizational skills.

• Strong eye for detail.

• Strong written, verbal and interpersonal communication skills.

• Extensive knowledge of applied statistics, analytics, machine learning, data science or big data tools (Microsoft SQL and SAS).

• Experience with Business Objects or other enterprise-class reporting software.

• Interest in taking initiative and helping the team discover problems and troubleshoot solutions.

• Ability to think creatively, embrace new approaches and pioneer innovative solutions to intricate problems.

• Ability to write reports and perform analysis quickly and accurately on large datasets.

• Experience working on multiple tasks and assignments while maintaining attention to detail, and the ability to be flexible with changing demands.

• Extensive knowledge of Outlook, and Microsoft Office Suite.

• Experience with Project Management software.

Public Service Loan Forgiveness

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/.

Residency Requirement

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.

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 individual's sex, race, color, ethnicity, national origin, age, religion, disability, sexual orientation, veteran status, gender identity, or pregnancy.