Data Scientist (Fraud Analytics)

TaxSlayer•Augusta, GA

20h•Remote

About The Position

Data Scientist (Fraud Analytics) Who We Are At TaxSlayer , were more than just a tax software companywere empowering individuals and small businesses to file their taxes online with confidence and ease. Since 1965, TaxSlayer 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, TaxSlayer 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. Are you a TaxSlayer? About the Role The Data Scientist (Fraud Analytics) designs, develops, and deploys actionable fraud detection models at TaxSlayer. This 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.

Requirements

Bachelors degree required; masters preferred in Data Science, Computer Science, Cybersecurity, or related field.
7+ years of experience in fraud detection and prevention, preferably in FinTech 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 (TensorFlow, 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.
Must be able to work at a computer for extended periods.

Responsibilities

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.

Benefits

Exempt Salaried employees receive a generous PTO bank, in addition to Paid Holidays.
Medical, Dental, and Vision insurance offerings from Aetna and SunLife. Options for Employee Only, Employee + Spouse/Domestic Partner, Employee + Children, or Family.
401K with 150% match on up to 3% contribution
Performance-based bonus and salary review process
Wellness Program
Life Insurance for employee
Long-term and Short-term disability
Critical Illness Insurance
Accident Insurance
Education Assistance
company-paid parking
on-site fitness facility
and a company store.