Top Remote Senior Level Jobs in Las Vegas, NV

Own analytical projects supporting revenue, profitability, and operational performance for the insurance business. Analyze funnels, campaigns, conversions, costs, and trends; build SQL queries and Looker dashboards; automate reporting with Python; define KPIs; validate data; and present actionable recommendations to stakeholders and leadership.

Drive new client acquisition and revenue through high-volume lead outreach, sales strategy, CRM pipeline management, client pitches, stakeholder engagement, pricing analysis, and cross-functional collaboration to meet sales targets.

Partners with business stakeholders and AI leadership to identify and evaluate workplace AI use cases, quantify business impact, develop buy-versus-build recommendations, and track adoption, performance, and ROI. The role analyzes workflows and operational data, creates baselines, dashboards, business cases, vendor comparisons, and executive-ready recommendations to guide AI implementation and adoption strategies.

Lead CTV media buying and programmatic strategy across Ashley’s furniture and mattress brands. Optimize campaigns, budgets, CPMs, audience targeting, and frequency to drive online conversions and in-store sales. Manage publisher, streaming platform, ad exchange, and DSP relationships; negotiate Deal IDs and PMP agreements; oversee attribution, incrementality testing, clean-room analysis, impression deduplication, and offline conversion measurement. Partner with data science and creative teams to improve performance, unify fragmented vendor data, and achieve ROAS targets.

Manage the post-sale client lifecycle for health insurance customers, including implementation, workflow design, dashboard analysis, ROI measurement, project management, and relationship building. Serve as the primary client contact while coordinating with Sales, Product, Data Science, and Engineering. Ensure clients successfully adopt and maximize the value of predictive analytics solutions through strong communication, documentation, and ongoing engagement.

Lead end-to-end SAP Concur Expense and Invoice implementations, including discovery, requirements gathering, solution design, configuration, testing, deployment, training, and post-production support. Advise clients on best practices, workflows, policies, reporting, process improvements, and system optimization. Serve as a subject matter expert, manage implementation projects, support demonstrations and RFPs, develop communications and training materials, and travel onsite to client locations as needed.

Own Jasper’s customer advocacy and experiential marketing engine, including customer story development, reference programs, analyst and press preparation, customer-generated content, and six annual Customer Advisory Boards. Build executive and practitioner relationships, design high-touch events, deploy customer proof into sales and post-sale programs, and measure product behavior change, account coverage, expansion pipeline, and advocacy conversion. Partner cross-functionally with Sales, Customer Success, Product Marketing, Marketing Ops, and RevOps in a fully remote role requiring 20–25% travel.

Own People Operations programs including benefits, HRIS, payroll, multi-state compliance, policies, performance and merit cycles. Manage vendors, administer HR systems, improve and automate processes, and support employee experience. Provide analysis and recommendations for future PEO, HRIS, benefits, and policy decisions while handling sensitive employee matters with tact and clarity.

Conducts independent AML and fraud investigations involving retail banking, brokerage, cryptocurrency, and virtual assets. Performs on-chain transaction tracing, evaluates sanctions and money-laundering risks, determines whether activity warrants Suspicious Activity Report filing, and documents case findings. Supports detection improvements, process enhancements, training, and ad hoc investigations while maintaining knowledge of BSA/AML, USA PATRIOT Act, OFAC, and virtual-asset regulations.

Own data science for customer-facing product features, including LTV prediction, experimentation, benchmarking, and forecasting. Proactively analyze data to identify customer problems and product opportunities, build and deploy production-grade models, and influence product roadmaps. Partner with Product, Engineering, and Analytics, communicate findings to varied audiences, iterate on shipped features, and lead new data-driven initiatives.