Data Scientist - Fraud Strategy

Job Description

Job Description: Data Scientist - Fraud Analysis

Location: Austin, TX / Boston, MA / Chandler, AZ / Chicago, IL / Conshohocken, PA / Los Angeles, CA / Miami, FL / New York City, NY / Omaha / La Vista, NE / Plymouth Meeting, PA / San Francisco, CA / San Jose, CA / Scottsdale, AZ / Washington, D.C. / Wilmington, NC

Job Type: Full-Time

Roles & Responsibilities:

As a member of the Fraud Analytics team, you will be responsible for identifying,

investigating, and mitigating fraudulent activities using advanced data methodologies:

Core Analytical & Comparison Tasks: Compare outputs of two systems or data

sources that should behave the same, isolate the differences, and document root

causes and thresholds.

Strategy & ML Collaboration: Investigate suspicious transactions to determine root

causes. Be comfortable working alongside an ML team and experienced in evaluating

model performance.

Fraud Assessment & System Development: Conduct in-depth assessments on

evolving trends (including merchant fraud, first-party, and third-party fraud). Design

and implement fraud rules within workflow systems and build comprehensive

monitoring reports.

Stakeholder Management: Generate high-impact reports and presentations for

management, outlining risks, incidents, and effective mitigation strategies.

Cross-Functional Collaboration: Partner with Risk, Operations, and Compliance

teams to strengthen the overall fraud prevention ecosystem.

Market Intelligence: Stay ahead of industry trends, regulatory shifts, and global best

practices to continuously refine fraud prevention strategies.

Technical & Professional Skills:

Domain Expertise: Proven experience in Fraud Mitigation, First-Party Fraud,

Transactional Fraud, Merchant Fraud, and Digital Fraud Detection.

Technical Stack: Proficiency in Python and SQL on BigQuery and Jupyter notebook

experience, then experience with rules management (reading, comparing, and

translating rule logic).

Analytical Rigour: Familiarity with fraud detection software, risk assessment

methodologies, and regulatory compliance standards.

Communication: Ability to distill complex data insights into clear, concise, and

actionable presentations for leadership.

Qualifications

Education: Bachelor’s degree in engineering, Technology, Computer Science, or a

related quantitative field.

Experience: 3+ years of dedicated data analytics experience specifically within fraud

prevention or risk management.

We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, citizenship status, age, disability, genetic information, protected veteran status, or any other characteristic protected by applicable law.

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