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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 Tax Policy & Data Analytics Division reviews, analyzes, and evaluates existing and proposed policies and legislation that affect the Department of Finance and New York City in general. This includes analyzing the revenue and distributional impacts of proposed changes to the tax system, monitoring and reporting on tax and parking revenues, working with local and state public agencies and private sector interests to promote improved tax administration, and advising the commissioner, Executive Office, and the New York City Office of Management and Budget on revenue and budgetary issues. The Tax Policy and Data Analytics Division is also responsible for all modeling and data mining for DOF’s Audit Division. Tax Policy also prepares briefing and position papers on tax policy and issues a variety of public reports and newsletters on tax-related issues.
Tax Policy and Data Analytics, Property Tax Analysis Unit, seeks an individual with strong quantitative economic and fiscal research skills with experience with data visualization to conduct end-to-end dashboard creation for not only this unit, but for the entire division.
Duties will include, but are not limited to:
– Manage data extraction, manipulation, transformation, and aggregation for a variety of projects pertaining to the real property tax system of New York City.
– Lead the creation of interactive and visually compelling Power BI reports and dashboards to meet business requirements for the unit and the Division.
– Develop and implement a comprehensive Power BI strategy aligned with the organization’s goals and business needs.
– Design and develop data models to support efficient data retrieval and analysis in Power BI.
– Implement data integration processes to bring data from various sources into Power BI datasets.
– Assist with a variety of fiscal impact analysis of property tax related legislation, including but-not-limited-to, circuit breakers, interest reduction programs and rebates.
– Presenting research findings to Senior Director and Assistant Commissioner on a regular basis.
– Mine large and complex datasets.
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
– A track record of strong quantitative research skills and intuition around analytics, including experience with descriptive statistics, predictive/inferential statistics, fiscal forecasting, etc.
– Experience with developing and optimizing complex SQL queries to manipulate data for analytics.
– Experience with deploying data analytics and data science solutions in R, SAS, or Python.
– Extensive experience working with data visualization tools, such as Microsoft Power BI.
– Experience in end-to-end dashboard creation: gathering requirements creating a data pipeline that merges data sources, manipulates, and cleans data producing a dashboard that effectively communicates the data iteratively integrating feedback from dashboard stakeholders and generating a finalized report that meets the requirements specifications.
– Experience in data quality control and reconciliation of large datasets, both within and across tables and application systems. Ability to detect and document data inconsistencies, investigate potential causes, and evaluate fixes.
– Experience presenting research findings to a variety of audiences including other analysts as well as non-technical audiences.
– Experience with Python packages related to data analytics (for example, matplotlib, numpy, scikit-learn) desired but not essential.
– Knowledge of containerization and version control (Docker, Github) and ETL approaches desired but not essential.
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.
