Data Scientist; Fraud Analytics

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At Tax Slayer
, we’re more than just a tax software company—we’re empowering individuals and small businesses to file their taxes online with confidence and ease. Since 1965, Tax Slayer has been revolutionizing the way people file taxes through our intuitive, user-friendly platform that guides customers step-by-step to ensure accuracy and maximize refunds.

Headquartered in Augusta, GA, with a satellite office in Charlotte, NC, Tax Slayer proudly employs nearly 200 year-round team members and 300 seasonal support agents. Our people are a talented group of innovators who work collaboratively to improve our products and exceed customer expectations year after year.

The Data Scientist (Fraud Analytics) designs, develops, and deploys actionable fraud detection models s role leverages advanced methods to identify, quantify, and mitigate suspicious behavior while maintaining a high-quality experience for legitimate users. The ideal candidate will collaborate with security, product, and compliance teams to support the development of robust fraud prevention controls.

What You’ll Be Doing

• Design, develop, and maintain production-ready fraud detection models, including supervised, unsupervised, and hybrid approaches.
• Partner with engineering to operationalize models developed from fraud vectors such as identity theft, refund fraud, account takeover, and abuse of tax credits.
• Engineer features from high-volume, multi-source datasets spanning user behavior, device signals, tax attributes, and payment data.
• Independently evaluate and select modeling approaches based on fraud typology, data availability, and operational constraints.
• Define and own model evaluation frameworks to include stability metrics and false-positive analyses.
• Conduct deep-dive analyses on fraud trends and report schemes.
• Translate analytical findings into actionable recommendations for fraud strategy, controls, and product changes.
• Ensure fraud models adhere to data privacy, security, and regulatory standards.
• Proactively communicate statuses, risks, and trade-offs to stakeholders where applicable.
• Maintain comprehensive documentation of model logic, assumptions, validations results, and known limitations.

Results You’ll Drive

• Improved detection rates for high-risk fraud scenarios without disproportionate increases in false positives.
• Reduced friction for low-risk users through accurate risk segmentation.
• Successful deployment and ongoing reliability of fraud models in production.
• Clear, audit-ready documentation to support regulatory review.
• Early identification and mitigation of model drift.

• Bachelor’s degree required; master’s preferred in Data Science, Computer Science, Cybersecurity, or related field.
• 7+ years of experience in fraud detection and prevention, preferably in Fin Tech or tax services.
• Expertise in model evaluation, validation, bias mitigation, and explainability in regulated domains.
• Strong experience with complex fraud scoring or high-throughput decision systems.
• Experience translating complex analytical concepts to technical and non-technical stakeholders.
• Strong project management and time management skills, with a demonstrated ability to prioritize high-impact work.
• Proven ability to work independently and drive initiative from concept to production.

• Advanced proficiency in ML frameworks (Tensor Flow, PyTorch).
• Advanced proficiency in Python, SQL, and data science libraries for modeling and analysis.
• Experience with model lifecycle management, version control, and reproducible experimentation.
• Demonstrated success developing and deploying complex fraud detection algorithms in production.

• This is a remote role.
• Work is performed in a standard office environment with minimal physical demands.
• Must be able to work at a computer for extended periods.

What we offer:

At Tax Slayer we realize the most important aspects in leading our industry are the bright minds behind…