Senior, Data Analyst - Last Mile Delivery - Fraud Detection

Position: (USA) Senior, Data Analyst - Last Mile Delivery - Fraud Detection
Position Summary...

What you'll do...

About the Role This role serves as the lead architect responsible for building, scaling, and optimizing fraud-detection capabilities across complex data ecosystems. It requires a blend of data analytics and behavioral science to architect relational data structures and ontologies while developing end-to-end SQL and Python pipelines (via fraud analytics tools) that power the detection engine. The core of the position involves developing risk-signal logic, building custom analytic applications, and experimenting with ML features and behavioral models to stay ahead of sophisticated threats.

Beyond technical infrastructure, this role holds the autonomy to make critical fraud deactivation decisions and the executive presence to present technical strategies and findings to senior leadership, ensuring the fraud-detection roadmap aligns with global business goals. What you'll do Fraud Detection & Behavioral Analysis
· Scaling Pattern Recognition:
Analyzes user behavior and platform interaction patterns at scale to identify unusual activity, suspicious accounts, and emerging fraud vectors.
· Core Analytic Execution:
Leverages fundamentals-including segmentation, trend analysis, anomaly detection, and correlation testing-to uncover sophisticated fraud patterns across massive, complex datasets.
· Risk Signal Synthesis:
Interprets mixed signals by synthesizing disparate data points such as GPS movement, device details, and behavioral metadata to build high-fidelity risk assessments.
· Contextual Intelligence:
Applies real-world context and considers cultural, social, and environmental factors to capture nuances that automated systems might overlook. Fraud Signal Development & Model Support
· Signal Engineering:
Builds and refines fraud indicators-including measurable behaviors, specific thresholds, and composite signals-for continuous monitoring through automated models and dashboards.
· Hypothesis Validation:
Identifies fraud motivations and opportunities, translating theoretical hypotheses into testable data signals and rigorous validation frameworks.
· Logic Optimization:
Stress-tests queries against legitimate user scenarios to refine logic, thresholds, and exclusion rules, effectively minimizing false positives.
· Strategic Enhancements:
Provides structured feedback and technical business requirements to drive the development of new fraud signals and the enhancement of detection tools. Investigation & Evidence Documentation
· Audit-Ready Documentation:
Executes structured investigation processes, maintaining clear, audit-ready case files that document every step from initial detection to the final deactivation decision.
· External Intelligence Integration:
Leverages open-source research (OSINT) to look beyond internal data ecosystems, confirming identities and uncovering external fraud clues or coordinated criminal networks.
· Defensible Reporting:
Prepares clear, defensible reports and technical documentation designed to stand up to rigorous internal audits or external legal settings.
· Adversarial Prototyping:
Anticipates system exploits by thinking like a bad actor, proactively identifying vulnerabilities to stay ahead of evolving fraud tactics. Cross-Functional Collaboration & Reporting
· Cross-Functional Insight Delivery:
Presents high-level operational insights to Product, Legal, Compliance, Engineering, and Care Operations to directly inform technical tooling improvements and policy updates.
· Strategic Decision Support:
Provides deep operational context that guides broader fraud-prevention strategies and critical product design decisions.
· Programmatic Gap Analysis:
Produces structured summaries of operational findings, QA trends, and SOP gaps to drive continuous program updates and process optimization.
· Compliance & Audit Governance:
Oversees all technical and operational documentation to ensure strict adherence to audit readiness and global compliance expectations. What you'll bring
· Educational Foundation:
Holds a Bachelor's degree in Criminal Justice, Data Analytics, Business, Information Systems, or a related technical field.
· Professional…