Top Analysis Reporting Jobs in Spokane, WA

Leads marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.

Maintain and administer Microsoft SQL Server databases supporting healthcare research administration, compliance, reporting, and operations. Design schemas and tables; develop and optimize stored procedures, queries, scripts, utilities, and reports; manage scheduled jobs; monitor performance, security, backups, recovery, and data integrity; troubleshoot database and application issues; coordinate with web developers; document solutions; and provide technical recommendations to research leaders.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Build and expand the company’s analytics data stack using Looker, LookML, dbt, BigQuery, and Airbyte. Develop data models, integrate multiple business systems, create KPI dashboards, and analyze product usage, customer health, adoption, and revenue data. The role empowers business teams with self-service analytics, actionable insights, and data-informed decision-making while developing a strong understanding of business metrics.

Conduct open-ended research on markets, companies, products, funding, competitors, technologies, people, and regulations. Transform findings into clear, sourced matrices, briefs, landscape maps, and one-pagers with actionable points of view. Use AI tools and lightweight scripts or scrapers to accelerate research, manage multiple shifting requests, and communicate concise conclusions to leadership.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Lead product experimentation and analytics across three product squads. Design experiments, define product metrics, analyze patient and clinician behavior, build dashboards, apply causal inference, and communicate actionable insights. Partner with product, engineering, design, clinical, operations, and data teams to improve instrumentation, data quality, and evidence-based healthcare product decisions.

Design and implement scalable, secure enterprise data solutions on Databricks and Azure using Delta Lake and Medallion Architecture. Lead and mentor data engineering teams; define integration patterns, governance, security (Unity Catalog, RBAC, masking, row/column-level security), and CI/CD/IaC practices. Ensure data quality, lineage, monitoring, and optimize Spark/Delta workloads for performance and cost while aligning solutions with business needs.