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.
DOF’s Property Exemptions Administration (PEA) oversees and executes property tax benefits for a diverse array of entities and individuals. PEA’s core responsibilities encompass the examination, processing, and management of applications for exemptions and abatements. These benefits extend to commercial and industrial properties, residential multi-family construction, new one- to two-family construction, government entities, and non-profits, as well as renters and homeowners, including members of the clergy, seniors, people with disabilities, and veterans. PEA is committed to ensuring the accessibility of property tax benefits for all eligible constituents.
PEA’s Data Analytics and Program Evaluation (DAPE) unit is responsible for integrating data analysis into the business operation of the division. The main goals of the unit are to establish an environment where efficient data analysis is performed on the modern platform, to develop and standardize statistical analysis and periodic reporting, to support the division-wide effort to evaluate and enhance program operations based on the current and evolving business needs, to provide data analysis to help establish the compliance mechanism. The unit is also responsible for providing policy analysis and recommendations from operational perspectives.
DAPE is seeking one individual with strong analytical skills to serve as the Exemption Data Analyst. The ideal candidate will enjoy working with data, is keen on analyzing complex systems/issues, and providing creative solutions. Reporting to the Assistant Commissioner of PEA, the selected candidate’s duties will include, but are not limited to the following:
- Conduct extensive analyses of property exemption related data, such as data on property valuation, tax exemptions and abatements, income tax, real property transfer tax, Social Security Administration deaths, and Census data.
- Perform statistical data analysis to evaluate program operations and their efficiencies as well as efficacies.
- Contribute towards research reports published by DOF.
- Provide business analysis to identify the areas of improvement to be made and offer a set of recommendations.
- Aid the compliance effort to validate exemption recipients' qualifications.
- Provide periodic and ad hoc reporting. Develop clear and concise reports and measurements.
- Provide SAS programming or other programming language, to develop analytic datasets, using extremely large datasets. Data preparation steps include cleaning and testing the data, creatively solving problems, and manipulating and restructuring the data.
- Present data analysis to senior staff in Property, and other divisions within DOF.
- Prepare procedure manuals, reports and documentation.
- May supervise subordinate staff conduct research/analysis on specific problems in program operations.
Additional Information:
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification document form upon hire.
This position may be eligible for remote work up to 2 days per week, pursuant to the Remote Work Pilot Program agreed between the City and the Collective Bargaining Unit representing employees serving in the civil service title.
BUSINESS RESEARCH & DATA ANALY - 13135
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.
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