Fraud Management College Aide

Department-of-Finance; New York (NY); On-site; USD 25,000 - 30,000; Full time

Job summary

NYC Department of Finance (DOF) invites applications for a Fraud Management College Aide within the CPSS unit. The role focuses on developing fraud analytics, building predictive models, and supporting data platforms.

You will work with Python or R, analyze large datasets, and contribute to Power BI dashboards used by analysts and executives. This paid student position emphasizes hands-on technical work in finance and public sector fraud prevention, with residency requirements and standard NYC

Qualifications

• Enrolled in a graduate program with focus on fraud prevention and analysis.
• Experience with Python or R and data science libraries.
• Familiarity with SQL and relational databases.
• Exposure to machine learning techniques and fraud detection metrics.
• Experience with cloud platforms (Snowflake, AWS, GCP, Azure) is a plus.
• Ability to clearly communicate findings to technical and non-technical audiences.
• Focus on fraud prevention and analysis.

Responsibilities

• Collaborate with CPSS staff to build/refine machine learning models to enhance fraud detection.
• Write tests and evaluate predictive models using Python or R.
• Analyze large transactional datasets to identify fraud patterns, trends, anomalies.
• Maintain/refine Power BI dashboards used by analysts and executives; expand modules.
• Conduct literature reviews and vendor research on fraud schemes and tools.
• Document modeling workflows and results for transparency and reproducibility.
• Assist onboarding of the enterprise data platform.
• Analyze payment channel prevention strategies for recidivist customers and design prevention solutions.

Skills

Graduate student

Python/R

SQL

ML basics

Cloud platforms

Communication

Fraud analytics

Education

Graduate studies in data science / CS / statistics

College/GRAD matriculation

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.

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.

DOF is actively engaged in developing best practices to counter the growth of online payment fraud in our online and mobile channels. DOF’s CPSS unit recently implemented several technologies and developed in-house models to identify patterns of fraud and prevent it before it occurs. The focus now is on enhancing and operationalizing these tools, improving workflows, and proactively identifying emerging fraud patterns.

Citywide Payment Services and Standards (CPSS) unit is the official provider of online and mobile payments to all City agencies, ensuring efficient and compliant revenue collection. CPSS also provides point-of-sale software, third-party and self-service payment kiosks for agencies' in-person locations and is responsible for managing the planning and implementation of credit and debit cards, eCheck, Paypal, and Venmo payments, including FMS integration, bank-to-book revenue reconciliation, and automation and PCI-DSS compliance. CPSS is seeking a Fraud Management College Aide to support this initiative. This is a hands-on, technical role ideal for students pursuing studies in data science, data analytics, or computer science who are passionate about public sector and fraud analytics.

Reporting to the Director of Technology, the selected candidate’s duties and responsibilities include but are not limited to the following:

• Collaborate with CPSS staff to build or refine machine learning based models to enhance fraud detection and identification of other anomalous payment trends.
• Write tests, and evaluate predictive models using Python or R.
• Analyze large transactional datasets to identify patterns, trends, and anomalies related to fraudulent activity.
• Assist in maintaining and refining Power BI dashboards used by analysts and executives. Collaborate with stakeholders to iterate and expand Power BI dashboard modules; and expand end-user querying capabilities.
• Conduct literature reviews and competitive research on emerging fraud schemes, prevention technologies, and vendor tools.
• Help document modeling workflows and results for transparency and reproducibility.
• Assist with the onboarding of the enterprise data platform.
• Assist in the analysis of payment channel prevention strategies that have targeted recidivist customers that have submitted numerous failed payments; design, document and implement prevention solutions.

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.

COLLEGE AIDE (ALL CITY DEPTS) - 10209

Minimum Qualifications

For Assignment Level I:
Matriculation at an accredited college or graduate school. Employment is conditioned upon continuance as a student in a college or graduate school.

For Assignment Level II (Information Technology):
Matriculation at an accredited college or graduate school. Employment is conditioned upon continuance as a student in a college or graduate school with a specific course of study in information technology, computer science, management information systems, data processing, or closely related field, including or supplemented by 9 semester credits in an acceptable course of study.

For Assignment Level III (Information Technology Fellow):
Matriculation at an accredited college or graduate school. Employment is conditioned upon continuance as a student in a college or graduate school with a specific course of study in information technology, computer science, management information systems, data processing, or other area relevant to the information technology project(s) assigned, including or supplemented by 9 semester credits in an acceptable course of study. Appointments to this Assignment Level will be made by the Technology Steering Committee through the Department of Information Technology and Telecommunications.

SPECIAL NOTE

Maximum tenure for all Assignment Levels in the title of College Aide is 6 years. No student shall be employed more than half-time in any week in which classes in which the student is enrolled are in session. Students may be employed full-time during their vacation periods.

Preferred Skills

• Currently enrolled in a graduate program in Data Science, Computer Science, Statistics, Economics, or a related field with focus on fraud prevention and analysis.
• Some experience working with Python or R, along with commonly used data science libraries.
• Familiarity with SQL and relational database concepts.
• Exposure to machine learning techniques, fraud detection use cases, and model evaluation metrics.
• Experience with cloud platforms (e.g., Snowflake, AWS, GCP, or Azure) is a plus.
• Ability to clearly communicate findings to both technical and non-technical audiences.
• Skilled in data science, particularly with a focus on fraud prevention and analysis.

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.