Top Tech Jobs & Startup Jobs in Seattle, WA

Lead fraud risk management, prevention, assessment, and operational improvement initiatives. Identify risks, develop mitigation strategies, coordinate stakeholders, manage dependencies, and drive recommendations through implementation. Research emerging fraud trends and create SOPs, governance frameworks, requirements, process documentation, executive briefings, presentations, and reports. Translate complex fraud topics into actionable guidance for technical, operational, and executive audiences.

Develop and deploy UiPath-based RPA solutions for internal and external clients. Responsibilities include requirements gathering, process documentation, automation development, testing, deployment, queue management, scheduling, exception handling, debugging, governance, and Center of Excellence support. The role also involves business process analysis, system design, process optimization, change management, tool selection, and collaboration with developers, analysts, testers, and consulting teams.

Supports DOJ financial operations through transaction review, payment validation, data quality analysis, suspended disbursement reviews, trend monitoring, internal control assessments, dashboards, and corrective-action tracking. Provides analytical insights and recommendations to leadership while ensuring compliance with federal financial requirements and improving debt-related processing and reporting.

Analyze and maintain recruitment, onboarding, workforce, participant, and program-performance data for the NIH DataForce Service Program. Develop trackers, dashboards, reports, and briefing materials; monitor participant lifecycle activities; identify data-quality issues, risks, trends, and process improvements; and support recurring monthly and quarterly analyses. Collaborate with program managers, mentors, coordinators, and government stakeholders while protecting sensitive information and ensuring Section 508 accessibility compliance.

Leads healthcare performance transformation consulting for hospitals and health systems. Designs and implements clinical effectiveness, operational optimization, workforce, supply chain, revenue management, and productivity programs. Manages complex multi-site engagements, budgets, workstreams, client relationships, business development, proposals, and delivery assurance. Mentors consulting staff and advises healthcare executives while supporting practice methodologies and growth.

Leads healthcare consulting engagements to improve clinical, financial, and operational outcomes for payer and provider clients. Responsibilities include workflow redesign, resource utilization improvement, data and business process analysis, complex analytics, project management, client relationship management, financial impact assessment, proposal development, and executive presentations. The role also supports business development, team leadership, and implementation of operational improvement initiatives, with travel up to 75%.

Develop and maintain Microsoft Power Platform solutions for a federal client, including Power Apps, Power Automate workflows, Power BI reporting, and SharePoint repositories. Manage records, conference requests, and SOP processes through automated intake, routing, approvals, audit trails, permissions, and reporting. Collaborate with stakeholders on requirements, demonstrations, and iterative delivery within an agile sprint model while maintaining data integrity, governance, and compliance.

Leads healthcare consulting engagements focused on financial, clinical, and operational improvement for hospitals and provider organizations. Performs data and business process analysis, develops recommendations, manages project deliverables, coordinates teams, presents results to executives, and supports proposals and business development. Uses Excel, Tableau, Power BI, and other tools to analyze large datasets, benchmark performance, identify savings opportunities, and improve operational processes.

Own end-to-end production data platforms, writing Python and SQL, designing AWS pipelines, modeling analytics data, and implementing quality and reconciliation controls. Make architecture decisions independently, ensure correctness and auditability, and use AI coding tools effectively. The role also supports applied AI initiatives including entity resolution, LLM-assisted analytics, embeddings, and anomaly scoring.

Develop AI and machine learning solutions for fraud, anomaly detection, semantic search, entity resolution, and investigative analytics. Build and operationalize models across structured and unstructured data using AWS data lakehouse services, generative AI, NLP, graph analytics, and document intelligence. Evaluate model performance, explainability, monitoring, and risk scoring while supporting production integration, dashboards, and investigative workflows. Collaborate with technical teams, investigators, stakeholders, and federal clients in an Agile environment.