Jobs at Extend

Designs and maintains scalable data pipelines, integrations, and foundational data models using Snowflake, dbt, and AWS. Establishes data quality, testing, governance, and documentation standards while supporting analytics, financial systems, and reporting. Partners with Engineering, Analytics, Finance, and Operations, leads technical decisions, improves development workflows, mentors teammates, and incorporates AI coding agents into engineering processes.

Own growth strategy and relationship management for major enterprise merchant accounts. Lead program launches, optimize performance, conduct executive business reviews, develop go-to-market and promotional strategies, manage budgets, identify ROI opportunities, and communicate customer needs to product teams. The role requires strong executive presence, analytical and presentation skills, cross-functional collaboration, and experience managing customer relationships and strategic programs.

Leads Finance Analytics, owning forecasting methodology, annual and long-range planning, financial modeling, performance management, unit economics, strategic decision support, and capital allocation analysis. Partners with executives and cross-functional teams on resource planning, pricing, investments, and business performance. Manages and mentors analysts while advancing AI-enabled finance processes and analytical standards.

Leads Extend’s regulatory compliance strategy for service contract and insurance programs across North America. Oversees licensing, regulatory examinations, audits, filings, terms and conditions, internal controls, reporting, and compliance governance. Advises executive leadership, regulators, auditors, and cross-functional teams; builds and develops the compliance organization; establishes KPIs; manages regulatory relationships; and modernizes compliance processes using AI and technology.

Develop revenue optimization and risk mitigation strategies using experimentation, causal inference, forecasting, Monte Carlo simulations, and machine learning. Build data pipelines, improve analytics infrastructure, generate insights for client-facing teams, and influence Product and Engineering roadmaps. The role requires strong strategic thinking, business impact orientation, and collaboration in a remote-first environment.

Analyze behavioral, transactional, and interaction data to identify fraud patterns and emerging threats. Develop monitoring frameworks, dashboards, and mitigation solutions; evaluate AI fraud-review decisions; and translate findings into prompt, rule, workflow, and machine-learning feature improvements. Collaborate with Fraud Operations and Machine Learning teams, participate in code reviews, and mentor junior analysts. The role requires strong SQL and Python skills, statistical analysis expertise, business judgment, and fraud analytics experience.

Build and ship full-stack fulfillment features covering refunds, replacements, reverse logistics, and servicing. Own features from design through deployment, release, and monitoring while developing scalable event-driven and AI-native applications. Build single-page applications, collaborate with designers and cross-functional teams, apply sound API and data modeling practices, and deliver AI/agentic features safely in production. Identify technical investments, communicate tradeoffs, and work independently through ambiguous problems.

Build and maintain invoicing, reimbursement, revenue recognition, claims, and financial reporting models using SQL and dbt. Reconcile merchant, operational, warehouse, and accounting data; investigate variances; validate expenses; and establish automated financial controls. The role also triages data issues, investigates production APIs, supports audits, partners on merchant configuration, and drives upstream fixes through root-cause analysis and automation.

Lead a team analyzing large-scale behavioral and transactional data to detect and prevent fraud. Build monitoring frameworks, dashboards, and metrics; track and optimize AI agent performance; partner with ML, product, and engineering to translate findings into model features; hire, mentor, and coach analysts; and define cross-functional fraud strategies.

As a Fraud Operations Specialist, you will investigate fraud cases, analyze risk scores, collaborate across departments, and improve fraud detection processes. You will use data analysis to ensure compliance and support the overall efficiency of claims management.

Lead end-to-end development of fraud and risk ML systems: define problems, engineer features, build and evaluate models, collaborate with product and engineering, deploy with ML engineers, and monitor production performance to detect drift and trigger retraining.