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The Senior Software Engineer II will work on AI-driven solutions, developing and deploying scalable applications while mentoring engineers and collaborating with cross-functional teams.

As a Product Manager II, you will drive product strategy, manage lifecycle from discovery to launch, and leverage user data for decision-making. You'll collaborate with cross-functional teams and advocate for AI integration to enhance the customer experience while refining the product roadmap.

Lead discovery, definition, and delivery of product features for merchants. Drive end-to-end lifecycle from PRDs to launch, use data, A/B testing, and user research, integrate AI where useful, collaborate with engineering and design, gather customer feedback, and prioritize roadmap and sprint activities.

Build and maintain auditable data pipelines in Snowflake and dbt to ensure financial reconciliation and audit readiness. Partner with Accounting, Operations, Engineering, and Reporting to investigate data issues, improve integrations via APIs, and own claim reimbursement and contract sales data workflows.

Support day-to-day HR operations including onboarding/offboarding, HRIS recordkeeping, benefits administration, performance cycle coordination, employee relations intake, People program coordination, reporting, and internal communications. Act as first point of contact for employees and managers, improve People processes using technology/AI, and help plan company events and People initiatives to enhance employee experience.

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.

Lead company-wide People programs, advise executives on org design and succession planning, optimize HR processes with data and automation, drive performance management, compensation, leadership development, manager enablement, and employee engagement while mentoring the People team and ensuring compliance.

Lead and build the Risk Analytics function: define pricing methodology and risk frameworks, own portfolio and pricing strategy, convert monitoring into decision systems, architect the Risk Analytics data layer (dbt/Snowflake), mentor senior data scientists, and represent risk recommendations to senior leadership to drive business decisions.

Lead cross-functional teams to identify and implement revenue-driving strategies. Own revenue optimization, develop quantitative analyses (A/B testing, causal impact), improve data pipelines and tracking, embed AI into workflows, and present insights to leadership to scale and recover revenue.

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.