Data Scientist - Fraud Strategy

Straive is hiring a Data Scientist for its Fraud Strategy team. The role focuses on validating parity across fraud rules engines and data sources, investigating discrepancies, and supporting loss-reduction initiatives using BigQuery and Jupyter notebooks.

Responsibilities

• 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
• Technical Stack Execution: Leverage heavy SQL on BigQuery and Jupyter notebooks to query,manipulate, and validate complex fraud data pipelines and rule logic
• 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

Skills

• Proven experience in Fraud Mitigation, First-Party Fraud, Transactional Fraud, Merchant Fraud, and Digital Fraud Detection
• Proficiency in Python and SQL on BigQuery and Jupyter notebook experience,then experience with rules management (reading, comparing, and translating rule logic)
• Familiarity with fraud detection software, risk assessment methodologies, and regulatory compliance standards
• Ability to distill complex data insights into clear, concise, and actionable presentations for leadership
• Detail-oriented with a proactive approach to problem-solving and a strong collaborative spirit for cross-functional success
• Bachelor's degree in Engineering, Technology, Computer Science, or a related quantitative field
• 3+ years of dedicated data analytics experience specifically within fraud prevention or risk management

Benefits

• Performance-based bonus plan
• Health, dental, and wellness benefits
• Continuous learning opportunities in modern AI and cloud-based financial platforms
• Collaborative and growth-oriented work environment
• Hybrid work arrangement in Chicago, IL

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