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Fraud Detection Machine Learning Jobs in Newark, DE

JPMorgan Chase & Co

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

... visual anomaly detection, synthetic data/image generation, and GenAI-enabled workflows-across ... Design and develop machine learning models to drive impactful fraud modeling, covering the entire ...

JP Morgan Chase

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

... visual anomaly detection, synthetic data/image generation, and GenAI-enabled workflows-across ... Design and develop machine learning models to drive impactful fraud modeling, covering the entire ...

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How much do fraud detection machine learning jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for fraud detection machine learning in Newark, DE is $17.65, according to ZipRecruiter salary data. Most workers in this role earn between $14.57 and $18.80 per hour, depending on experience, location, and employer.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What are some common challenges faced by professionals working in fraud detection machine learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What are the key skills and qualifications needed to thrive as a fraud detection machine learning specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What job categories do people searching Fraud Detection Machine Learning jobs in Newark, DE look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Newark, DE are:

Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in Newark, DE as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $36,709 per year, or $17.6 per hour.

Quant Analytics Associate I - Fraud Strategy

JPMorgan Chase & Co.

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 6 days ago

JPMorgan Chase & Co. rating

7.9

Company rating: 7.9 out of 10

Based on 500 frontline employees who took The Breakroom Quiz

78th of 175 rated banks

Job description


Drive impactful fraud prevention as a Quantitative Analytics Associate on our Point of Sale Fraud team-where your advanced risk analyses and strategic insights help reduce fraud losses, protect customers, and influence key decisions across the organization.
As a Quantitative Analytics Associate in the Point of Sale Fraud team, you will manage fraud risk strategies in the Fraud Policy area and perform complex risk analyses with the objective of reducing fraud related losses while balancing customer impact. You will frequently interact and communicate with cross-functional partners and communicate and present presentations to managers and executives.
Job Responsibilities:
  • Interpret large amounts of complex data to formulate problem statement, concise conclusions regarding underlying risk dynamics, trends, and opportunities
  • Manage, develop, communicate, and implement optimal fraud strategies (including rules, cutoffs, policies, operational flows, etc.) to protect the bank from fraud related losses and improve customer experience at Point of Sale
  • Identify key risk indicators and metrics, develop key metrics, enhance reporting, and identify new areas of analytic focus to better capture fraud.
  • Provide subject matter expertise on strategy implementation/testing and initiatives related to the improvement of risk mitigation processes and infrastructure
  • Collaborate with cross-functional partners to understand and address key business challenges
  • Identify business opportunity by performing well thought analysis - Data mining, ensuring data integrity, synthesizing and communicating findings to senior management
  • Assist team efforts in the critical development of new fraud pattern or spending pattern detection tools while providing clear/concise oral and written communication across various functions and levels, inclusive of Operations, IT, and Risk Management

Required Qualifications, Capabilities, and Skills:
  • Bachelor's degree (or related work experience) in a quantitative discipline in a financial services organization and 2 or more years' experience in fraud/risk/payments or related field.
  • Advanced understanding of Python, SAS, and SQL.
  • Ability to query large amounts of data and transform raw data into actionable management information.
  • Strong analytical and problem-solving abilities.
  • Experience delivering recommendations to management.
  • Self-starter with the ability to drive for resolution.
  • Strong communication and interpersonal skills with the ability to interact with individuals across departments/functions and with senior-level executives.

Preferred Qualifications, Capabilities, and Skills:
  • Master's degree (or related work experience) in a quantitative discipline, preferably in a financial services organization, plus 2 or more years' experience in fraud/risk/payments or related field.
  • Experience with Machine Learning technologies and knowledge of LLMs.

This role is not eligible for visa sponsorship now or in the future. Sponsorship includes, but is not limited to, support for I-983 training plans, F-1/OPT or CPT, H-1B, and any other employment authorization or immigration-related action requiring JPMorganChase sponsorship or intervention
About Us
Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans
About the Team
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions - all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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