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
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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. xhqgsiq
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.
Data Scientist - Fraud Analysis in new york at Unknown Company
This position is listed as full time and onsite.