Overview
Job Description
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.
Property Valuation and Tax Mapping is responsible for valuing more than one million properties in the city and overseeing assessments and valuations in a fair and equitable manner. The valuations enable the efficient and effective collection of property tax revenues for New York City.
The Property Data Analytics Reporting & Planning (PDARP) Group, reporting directly to the Assistant Commissioner of Property, provides research and analytical support for executive initiatives by operationalizing new workflow techniques, providing tools to assessors and field valuation that leverage technology through statistical summaries, designing summary data analyses and quality control reports based on extremely large datasets, property valuation, modeling, spatial analyses, and map driven data pulls. The selected candidate will report directly to the PDARP Director.
Responsibilities include, but are not limited to, the following:
– Conduct extensive research and analyses of property related data, including, but not limited to, sales, cost, market trends, economic conditions and other factors impacting value using statistical analyses and econometric modeling techniques.
– Use SAS, SQL, or another programming language to perform summary data reporting using large datasets and critically analyze statistical findings.
– Respond to ad-hoc data summary reporting and statistical analyses requests, data mapping requests and assessment review projects.
– Ensure statistical data analyses and data summary report quality by implementing quality control measures.
– Assist with the development of procedure manuals, reports and documentation.
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.
– Proficiency using SAS or another programming language (Stata, R, SPSS, or others). – Experience with statistical/econometric data modeling techniques and regression analyses. – Strong programming, data analyses experience working with large datasets. – Experience using ARCGIS or other geographic information systems software. – Experience using relational databases, data mining and extracting data using SQL. – Proficiency in MS Word, Excel, and PowerPoint. – Strong interpersonal and teamwork skills with ability to work independently. – Strong quantitative analytical skills and attention to detail.
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.
