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Fraud Detection Machine Learning Jobs in Delaware

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Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection ... Learn and understand a large body of research in deep learning and machine learning * Participate ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Delaware

Fraud Detection Machine Learning information

See Delaware salary details

$10

$18

$26

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

As of Aug 13, 2026, the average hourly pay for fraud detection machine learning in Delaware is $18.07, according to ZipRecruiter salary data. Most workers in this role earn between $14.90 and $19.23 per hour, depending on experience, location, and employer.

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 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 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 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 are popular job titles related to Fraud Detection Machine Learning jobs in Delaware?

For Fraud Detection Machine Learning jobs in Delaware, the most frequently searched job titles are:

What job categories do people searching Fraud Detection Machine Learning jobs in Delaware look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Delaware are:

What cities in Delaware are hiring for Fraud Detection Machine Learning jobs?

Cities in Delaware with the most Fraud Detection Machine Learning job openings:

Fraud Detection Machine Learning jobs near you
Infographic showing various Fraud Detection Machine Learning job openings in Delaware 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 $37,580 per year, or $18.1 per hour.

Quantitative Analytics Associate - Fraud Prevention Optimization Strategy

JPMorgan Chase & Co

Wilmington, DE • On-site

Full-time

Medical, Retirement

Re-posted 4 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description

Are you interested in joining a dynamic team? Become a Quantitative Analytics Associate on our Consumer and Community Banking (CCB) Fraud Prevention Optimization Strategy team to reduce cost of fraud and improving customer experience. The breadth of experiences, learnings, and connections in this role will enable your growth and development. To excel, you'll be highly motivated, highly analytical, extremely detail oriented, and an exceptional problem solver who takes pride in being part of an organization that owns customer issues from beginning to end and delivers accurate, timely solutions. 

As a Quant Analytics Associate I in our Fraud Prevention Optimization team you will focus on reducing cost of fraud, through complex analyses combined with business insights and collaboration. Your objective is reducing losses and / or operating expenses while balancing customer impact through optimizing business processes and decisioning. You will frequently interact and communicate with cross-functional partners and present complex analysis succinctly to managers and executives. You will be provided an opportunity to be part of a dynamic team that is instrumental in protecting the bank by leveraging complex analytics and new tools like large language models to deliver sustainable, hard hitting business improvements.

Job Responsibilities

  • Interpret and analyze complex data to formulate problem statement, provide concise conclusions regarding underlying risk dynamics, trends, and opportunities.
  • Use advanced analytical & mathematical techniques to solve complex business problems. 
  • Manage, develop, communicate, and implement optimal fraud strategies to reduce fraud related losses and improve customer experience across credit card fraud lifecycle. 
  • Identify key risk indicators, develop key metrics, enhance reporting, and identify new areas of analytic focus to constantly challenge current business practices.
  • Provide key data insights and performance to business partners.
  • Collaborate with cross-functional partners to solve key business challenges.
  • Assist team efforts in the critical projects while providing clear/concise oral and written communication across various functions and levels.
  • Champion the usage of latest technology and tools, such as large language models, to drive value at scale across business organizations.

Required qualifications, capabilities, and skills

  • Bachelor's degree in a quantitative field or 3 years risk management or other quantitative experience
  • Background in Engineering, statistics, mathematics, or another quantitative field 
  • Advanced understanding of Python, SAS, and SQL
  • Query large amounts of data and transform into actionable recommendations.
  • Strong analytical and problem-solving abilities
  • Experience delivering recommendations to leadership.
  • Self-starter with ability to execute quickly and effectively.
  • Strong communication and interpersonal skills with ability to interact with individuals across departments/functions and with senior level executives

Preferred qualifications, capabilities, and skills

  • MS degree in a quantitative field or 4 or more years risk management or other quantitative experience.
  • Hands on Knowledge of AWS and Snowflake.
  • Advanced analytical techniques like Machine Learning, Large Language Model Prompting or Natural Language Processing will be an added advantage.
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

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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