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Fraud Data Scientist Jobs in Delaware (NOW HIRING)

CCB Risk Program Associate

Wilmington, DE · On-site

$57K - $57K/yr

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

Fraud Product Owner

Newark, DE · On-site

$92K - $156K/yr

Partner with fraud strategists, operations and data scientists to build business requirements, procedures, and processes, including project planning, resource management, and process design.

Partner with fraud strategists, operations and data scientists to build business requirements, procedures, and processes, including project planning, resource management, and process design.

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Showing results 1-20

Fraud Data Scientist information

See Delaware salary details

$46K

$165.2K

$243.7K

How much do fraud data scientist jobs pay per year?

As of Aug 11, 2026, the average yearly pay for fraud data scientist in Delaware is $165,160.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,600.00 and $170,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the fraud data scientist position, and why are they important?

To thrive as a Fraud Data Scientist, you need strong analytical skills in statistics, machine learning, and data analysis, typically backed by a degree in data science, mathematics, or a related field. Familiarity with programming languages like Python or R, experience with SQL databases, and knowledge of fraud detection tools such as SAS, Hadoop, or relevant certifications like CFE are highly valued. Excellent problem-solving ability, communication skills, and the capacity to work collaboratively with cross-functional teams are important soft skills. These abilities are crucial for identifying and mitigating fraudulent activities while ensuring clear collaboration and actionable insights in a high-stakes financial environment.

What is a fraud data scientist?

A Fraud Data Scientist analyzes transactional and behavioral data to detect, prevent, and mitigate fraudulent activities. They use machine learning models, statistical analysis, and anomaly detection techniques to identify suspicious patterns in financial, e-commerce, or other data-heavy industries. Their role involves working with large datasets, collaborating with fraud investigators, and continuously improving fraud detection systems to minimize financial losses and risks.

What are the typical daily responsibilities of a fraud data scientist?

A Fraud Data Scientist's day often involves analyzing large datasets to detect suspicious patterns, developing and validating machine learning models to predict fraudulent activity, and collaborating with other teams such as compliance and risk management. Additionally, they may respond to real-time fraud alerts, participate in meetings to refine detection strategies, and prepare reports for stakeholders. The role combines technical analysis with ongoing learning about emerging fraud trends, making every day dynamic and intellectually challenging. Teamwork and adaptability are essential, as you'll frequently coordinate with engineers and business leaders to continually enhance fraud prevention efforts.

How much do fraud data scientists make?

Fraud data scientists typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and fraud detection tools can earn higher salaries, often exceeding $150,000.
What are popular job titles related to Fraud Data Scientist jobs in Delaware? For Fraud Data Scientist jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Fraud Data Scientist jobs in Delaware look for? The top searched job categories for Fraud Data Scientist jobs in Delaware are:
What cities in Delaware are hiring for Fraud Data Scientist jobs? Cities in Delaware with the most Fraud Data Scientist job openings:
Infographic showing various Fraud Data Scientist job openings in Delaware as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $165,160 per year, or $79.4 per hour.

Senior Loans Fraud Data Analyst

OneMain Financial

Wilmington, DE

$83K - $105K/yr

Full-time

Medical, Retirement, PTO

Posted 17 days ago


OneMain Financial rating

7.4

Company rating: 7.4 out of 10

Based on 101 frontline employees who took The Breakroom Quiz

117th of 150 rated financial services


Job description

The Senior Loans Fraud Data Analyst will be accountable for fraud strategy analytics for branch/digital loan acquisitions and transactions spanning OneMain's Personal Loans and Auto businesses. It is an exciting opportunity for someone looking to build and truly influence fraud defenses across a variety of originations channels and methods in a growing and evolving organization.The candidate will be responsible for supporting analytics that drive fraud strategy performance and execution, ensuring we are balancing between reducing fraud and maintaining minimum user friction. Working with various partners, the role will also have responsibilities for fraud reporting to senior leadership, strategy implementation, testing and validation, and, as need arises, ad-hoc analyses.

A successful candidate must love digging into the details and have a passion for deriving data-driven insights. This role requires being both proactive and reactive - understanding what the next question may be, while adapting to real-time issues and needs. Though most time will be spent in data and strategy development, there will be opportunities to interface with other teams (Operations, Technology, Compliance) to align with broader organizational initiatives.

In the Role

  • Prepare and present regular fraud performance reporting and analytics results to management and business partners.
  • Support development and execution of fraud acquisition strategies that balance loss prevention, sales growth, and customer experience.
  • Optimize operational efficiency of manual reviews.
  • Collaborate with business partners to ensure fraud strategies are implemented accurately and on-time.
  • Optimize existing verification and fraud processes to improve customer experience and decrease losses.
  • Identify, verify and analyze data defects/issues and communicate with the appropriate team to determine the root cause for issue resolution.
  • Execute ad-hoc data process jobs to enhance fraud prevention efforts.
  • Responsible for develop/updating routine reporting such as Monthly Fraud KPI reporting, vendor performance reporting...etc.
  • Leverage MS Power BI along with advanced data mining techniques to develop and maintain operational performance dashboards for Enterprise Fraud Group
  • Responsible for linking analysis of incoming apps based on customer's matching data and produce reports highlighting suspected applications to support Enterprise Fraud Group in investigating fraud on daily basis (15%).
  • Responsible for managing and monitoring Fraud Schema database

Requirements

  • Bachelor's degree in a quantitative discipline such as Statistics, Economics, Business Management or Computer Science; Master's Degree preferred.
  • Minimum 3+ years' experience in quantitative risk analytics (credit card or personal loans); preferably at a financial institution, auto/fraud experience a plus.
  • Advanced programming skills and knowledge in analytics and statistic tools (e.g. SAS, SQL, Python).
  • Experience utilizing data visualization tools (Tableau, Power BI, or equivalent).
  • Proficient knowledge of Microsoft Excel/PowerPoint.
  • Excellent quantitative and analytic skills; ability to derive patterns, trends and insights, and perform risk/reward trade-off analysis.
  • Ability to work independently and within a team setting with minimal direction/supervision.
  • Extremely detail-oriented; intellectual curiosity.
  • Ability to multi-task and work against tight deadlines.
  • Experience with writing originations strategies and leveraging third party decision platforms.

Location: Wilmington, DE;

Who we Are

OneMain Financial (NYSE: OMF) is the leader in offering nonprime customers responsible access to credit and is dedicated to improving the financial well-being of hardworking Americans. Since 1912, we've looked beyond credit scores to help people get the money they need today and reach their goals for tomorrow. Our growing suite of personal loans, credit cards and other products help people borrow better and work toward a brighter future.

Driven collaborators and innovators, our team thrives on transformative digital thinking, customer-first energy and flexible work arrangements that grow lives, careers and our company. At every level, we're committed to an inclusive culture, career development and impacting the communities where we live and work. Getting people to a better place has made us a better company for over a century. There's never been a better time to shine with OneMain.

Because team members at their best means OneMain at our best, we provide opportunities and benefits that make their health and careers a priority. That's why we've packed our comprehensive benefits package for full- and some part-timers with:

  • Health and wellbeing options for team members and their dependents
  • Up to 4% matching 401(k)
  • Employee Stock Purchase Plan (10% share discount)
  • Tuition reimbursement
  • Continuing education
  • Bonus eligible
  • Paid time off
  • Paid volunteer time
  • And more

OneMain Holdings, Inc. is an Equal Employment Opportunity (EEO) employer. Qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship status, color, creed, culture, disability, ethnicity, gender, gender identity or expression, genetic information or history, marital status, military status, national origin, nationality, pregnancy, race, religion, sex, sexual orientation, socioeconomic status, transgender or on any other basis protected by law.


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