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Fraud Detection Machine Learning Jobs in Delaware

JP Morgan Chase

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

Design and develop machine learning models to drive impactful fraud modeling, covering the entire ... monitoring, drift detection, and end-to-end auditability. Preferred Qualifications * Strong ...

Whiterabbit.ai

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 ...

Whiterabbit.ai

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 ...

Whiterabbit.ai

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 ...

Whiterabbit.ai

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 Jul 23, 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 July 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $37,580 per year, or $18.1 per hour.
Senior Associate, Fraud Strategy Analyst

Senior Associate, Fraud Strategy Analyst

Sallie Mae

Newark, DE • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 hours ago

Sallie Mae rating

6.8

Company rating: 6.8 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

Job description

When you join Sallie Mae, you become a champion for all students.
We're on a mission to power confidence as students begin their unique journey. To help them plan their higher education, successfully finish, and prepare for life after school. To help them Start smart. Learn big.
Students need guidance navigating this important time in their life. They need someone who acknowledges that their education path is unique. They need a partner willing to evolve and not only meet but surpass their expectations. We're changing. Because students need a better way.
We're looking for people who are excited to drive this transformation. To break barriers and think of new ways to adapt, help, and create better experiences for students-and for each other.
This is where diverse backgrounds, beliefs, and perspectives matter. It's where you're empowered to bring your authentic self to work.
Feeling your best allows you to do your best. Our benefits take care of the whole you-from physical and mental to financial and professional. You'll get opportunities to further your education and career, support for you and your family (including your pets!), paid time off to volunteer for the things that matter to you, and more.
We're obsessed with impact and making a real difference. For us, that means putting relationships first, asking "why not?" when tackling challenges, and continuously learning new skills.
Come do more than join something, change something. For students, for future generations, for the future of education.
What You'll Contribute
As the Fraud Strategy Senior Associate, you will support fraud analytics and strategy initiatives, working closely with fraud, analytics, and cross-functional partners to analyze data, generate insights, and drive data-driven fraud decision-making. This role is responsible for helping design, implement, and continuously optimize fraud strategies to mitigate risk while supporting business objectives.
What You'll Do
  • Support fraud and analytics teams in conducting data analysis, modeling, and reporting to deliver insights and actionable recommendations related to fraud risk and strategy performance.
  • Create, implement, and optimize fraud strategies using data-driven insights, including evaluating effectiveness, monitoring performance, and identifying enhancement opportunities.
  • Gather, clean, and prepare data for analysis, ensuring accuracy and consistency across fraud and analytics use cases.
  • Develop models and forecasts to support fraud risk assessment, strategy tuning, and broader business planning and decision-making.
  • Monitor key fraud metrics and trends to identify emerging risks, strategy gaps, and opportunities for improved detection and prevention.
  • Create presentations summarizing findings and provide clear, well-supported recommendations to leadership to influence fraud and business strategy decisions.
  • Create and maintain data documentation, data dictionaries, fraud strategy documentation, and standard operating procedures as needed.
  • Contribute to the continuous improvement of data quality, data governance, and fraud strategy management processes.

The above information is intended to describe the general nature and level of work performed by employees assigned to this job; it is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities, and qualifications required of employees in this role.
What You Have
Minimum: Indicate minimum education, skills and experience required.
  • Experience with SQL, Python, R, or other programming languages commonly used in analytics and fraud analysis.
  • Strong attention to detail with the ability to deliver high-quality, accurate work in a risk-sensitive environment.
  • Excellent communication skills, with the ability to present complex data and fraud concepts clearly and concisely to stakeholders at all levels of the organization.
  • Strong problem-solving and critical-thinking skills, particularly in evaluating risk tradeoffs and strategy effectiveness.
  • Demonstrated ability to work collaboratively across departments and functions, including fraud, analytics, technology, and business partners.
  • Familiarity with data visualization tools such as Tableau, Power BI, or similar platforms.
  • Experience in e-commerce or retail analytics is preferred.

Preferred Qualifications
  • Bachelor's degree in mathematics, statistics, economics, computer science, or a related field.
  • Three (3) years of experience in analytics, fraud strategy, fraud operations, or a related field.

Feeling your best helps you do your best:
Our benefits take care of the whole you-so you can build your work around your life (not the other way around!).
  • Competitive base salaries
  • Bonus incentives
  • Generous PTO, Floating Holidays and 12 Federal Holidays observed
  • Support for financial-well-being and retirement 401k with employer match
  • Comprehensive medical, dental, vision, hospital indemnity, critical illness, pet insurance and more
  • Employer paid short-term/long-term disability and basic life insurance
  • Flexible hybrid working arrangements.
  • Paid parental leave and adoption reimbursement programs
  • Free access to on-site staffed fitness centers (in Delaware) and gym subsidy (for locations outside Delaware)
  • Confidential counseling support (EAP), Health Advocacy services and Wellness program with financial incentives
  • Tuition Reimbursement and Family Scholarship Programs
  • Career development and training opportunities

Not the right fit? Let us know you're interested in a future opportunity by clicking Introduce Yourself in the top-right corner of the page or create an account to set up email alerts as new job postings become available that meet your interest!
Sallie Mae is proud to be an equal opportunity (EEO) employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, sexual orientation, national origin, age, genetic information, gender identity, disability, Veteran status or any other characteristic protected by federal, state or local law. Click here to view the U.S. Pay Transparency Policy, here for federal job applicant notices, and here to view the California Employee Privacy Notice.
Reasonable accommodations are available for applicants with disabilities in all phases of the application and employment process. To request an accommodation please call (855) 756-2007 and choose option 9. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

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