Deputy Director, Data Analytics

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 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 perform account adjustments and respond to refund inquiries from the public. The Payment Technology unit seeks a thoughtful, dynamic, motivated individual, to serve as the CityPay Deputy Director of Data Analytics. With an interest in city government, the ideal candidate will use data to positively benefit the public. Additionally, the ideal candidate will use data to help inform and drive the decision-making process, and inform strategies for efficient revenue collection, cost reduction, fraud mitigation, and predicting customer payment trends and behaviors. This position offers the opportunity to work with data analysts and staff across multiple City agencies and vendors. Reporting to the Director of Payment Technology, the selected candidate’s duties and responsibilities will include, but are not limited to the following: - Supervise and mentor interns and, potentially, junior data analysts in the unit, providing guidance and support in the areas of fraud analytics and other technologies related to operational data. - Work closely with business owners and product managers to build and maintain ongoing analysis of their products, usage patterns and performance. - Write database queries and code to analyze payment service usage volumes, user behaviors and performance data to identify opportunities and areas for improvement. - Collaborate with other staff and analysts to create and maintain dashboards; where necessary and feasible, create and maintain other proprietary products for end users to fulfill specific business data service needs. - Import data from external sources using Python scripting and export into formats that can be used for further manipulation by abroad set of division stakeholders with varying levels of experience, including executive staff. - Create visual products such as charts, heat maps, and other visual infographics that illustrate data trends for a broad set of division stakeholders with varying levels of experience, including executive staff. - Manage and maintain consolidated database of payments and transactional information from vendors, other business units, and legacy systems. - Research, compile, investigate and analyze large quantities of data from a variety of sources, with an eye to identifying policy and operational implications. - Communicate clearly and responsively your findings to a range of stakeholders, including management and executives. - Develop key performance indicators and metrics for payment service delivery and products. - Support current automated data processes and reports and develop automation for manual data processes. - Recommend and implement improvements to collection, processing, flow and distribution of data. - Document current procedures around data collection, processing and database management and editing. - Administer a SQL Server Data Warehouse, gathering data from diverse platforms, such as Vendor Portals, FTP Servers, Oracle Production DB, and API calls. - Develop and maintain scalable ETL pipelines on a RHEL (Red Hat Enterprise Linux) server using Python and shell scripts, with workflow scheduling and orchestration managed through cron jobs. - Create and manage a Power BI workspace, design reports/dashboards for DOF Commissioner and senior management, and several other TPS units as well as other DOF units, and external agencies, including OMB. This tool has been heralded for providing intuitive insights into informed policy decisions. - Collaborate with law enforcement agencies (local, state, federal)) to conduct ad hoc analyses, identifying and locating fraudsters on CityPay Site. Provided crucial clues and guided investigations effectively. - Monitor and report on the performance of Fraud Detection technologies implemented on CityPay online and mobile platforms. (Ravelin, Fraud Detect, Account Validation, Blocked Plates etc.) - Perform Quality Assurance (QA) processes for database testing, identifying data issues, and anomalies. Effectively communicate data scenarios to both business and technical teams, ensuring data accuracy and integrity. - Develop predictive models utilizing machine learning (ML) and artificial intelligence (AI) tools to help identify consumer payment and fraud patterns and trends. 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. 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.