Top Analytics Jobs in Portland, OR

Perform senior-level analysis on complex healthcare and business datasets (claims, utilization, financials). Design and maintain reports, dashboards, and ETL processes with SQL/SSRS/Excel; ensure data quality; build forecasts and models; lead projects; present insights to stakeholders; support audits and regulatory requests.

Designs and implements big-data data management solutions (Cloudera/Hortonworks/Databricks). Builds and automates reporting and analytics using SQL and Databricks, optimizes queries, manages ETL, integrates multiple data sources, enforces data governance, and supports payment integrity reporting requirements.

Analyze healthcare and operational datasets to create, validate, and maintain reports and dashboards using SQL, Excel, and BI tools. Support utilization, cost containment, regulatory reporting, and ad hoc analyses. Collaborate with stakeholders to define requirements, document workflows, and deliver actionable recommendations.

Lead analytics for quality and HEDIS performance improvement: design and build reporting, track HEDIS rates and interventions, conduct statistical analysis and predictive modeling, manage data warehouse changes, support audits and special projects, and train stakeholders on analytic solutions.

Lead pricing strategy and analytics: develop pricing, packaging and monetization recommendations; build forward-looking revenue/volume models; maintain pricing algorithms and reporting; collaborate with Sales, Finance, Marketing and Data teams to implement pricing actions and standardize quantitative outputs.

The Senior Manager of Risk Analytics will lead credit risk strategies, manage portfolio performance, optimize decisioning frameworks, and drive business growth through analytics and predictive modeling.

Translate web and marketing behavior data into actionable insights: measure website and marketing performance, analyze funnels and journeys, design and evaluate A/B tests, build reports and dashboards, monitor analytics integrity, and partner with cross-functional teams to define measurement and optimization opportunities.

The Data & Analytics Leader will develop a multi-year roadmap to enhance data governance and analytics capabilities, while fostering a data-driven culture throughout ERAC.

Lead analytics for Wealth Solutions: analyze client segmentation, revenue, and operational data; build models for capacity and workforce planning; produce insights and recommendations for senior leadership; partner with BI and Finance to improve advisor productivity, client experience, retention, and revenue growth; support strategic projects and translate complex data into clear presentations.

The Analytics Architect will design and implement cloud-based analytics solutions, maintain data pipelines, ensure data quality, and collaborate with teams to enhance operational efficiency.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

Hands-on technical lead designing and delivering scalable, secure Azure-based BI and analytics solutions. Own end-to-end Power BI architecture, mentor engineers, guide implementations, optimize performance, and advise clients on governance, deployment, and AI-augmented analytics. Drive discovery, backlog priorities, cross-team alignment, reusable assets, and consulting pursuits.

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.

Own growth and player behavior analytics across sportsbook, casino, and poker. Partner with Revenue Ops, Marketing, Product, and VIP to run retention, bonus optimization, segmentation, A/B testing, and predictive modeling using SQL, Snowflake, ML/AI tooling, and Python. Turn analysis into actionable recommendations and measurement frameworks.

Bridge enterprise customers' legacy BI to Hightouch by reverse-engineering complex marketing reports, building reusable reporting frameworks, engineering and documenting semantic/context layers, ensuring accurate SQL generation, and training non-technical marketers while collaborating cross-functionally to deliver reliable, idempotent AI-driven analytics.

Design and maintain scalable dbt data models and Looker dashboards; partner with Finance, Product, and GTM to translate requirements into analytics solutions; ensure data quality with Data Engineering; perform analyses, forecasting, and QA to deliver trusted reporting and drive analytics initiatives.

Own and evolve the analytics engineering platform: design and maintain certified dbt models, enforce modeling/testing/documentation standards, build semantic and metadata layers, optimize Snowflake performance, partner with analysts and data engineering to migrate business logic and ensure reliable, AI-ready analytics, and mentor teammates on analytics engineering best practices.

Lead and grow an analytics engineering team to build a trusted semantic metrics layer, scalable dimensional models, and governance. Partner cross-functionally to deliver reliable data products, improve pipelines and observability, set technical standards, and enable self-service analytics, experimentation, and ML while balancing scalability and business impact.

Perform default reporting and analytics for mortgage servicing portfolios, validate and troubleshoot data and exception reports, conduct root-cause analysis, produce ad-hoc reports, document processes, and collaborate with default management to ensure regulatory-compliant, accurate reporting delivery.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Own and build customer health, usage/adoption, and product configuration data models. Produce ad-hoc and recurring analyses to identify upsell/expansion opportunities, partner with CS, Sales, Product, and Data teams, and present actionable insights to leadership to drive revenue-relevant actions.

Lead end-to-end funnel analytics and optimization for SMB lending, identifying friction and bottlenecks, designing measurement frameworks, running experiments (A/B testing), and partnering with Risk, Operations, Product, Engineering, and AI teams to deploy automation and AI solutions that improve conversion, cycle time, and customer outcomes while managing risk.

Hands-on engineering role to design, build, and maintain scalable ETL/ELT data pipelines, data warehouses and lakes, and data models. Optimize batch and near-real-time processing, implement query optimization and data quality checks, support AI data workflows, and collaborate with architects, analysts, and stakeholders.

Lead Adobe Analytics architecture and MarTech ecosystem design, implement data layers and tagging across web and mobile, ensure QA and privacy compliance, enable reporting and audience activation, and drive cross-functional measurement and governance for personalization and optimization.

Design and implement a scalable Elasticsearch-based analytics platform integrated with an Oracle data warehouse. Architect data models, ingestion/CDC pipelines, index/shard strategies, and monitoring. Optimize cluster, queries, and caching for sub-second dashboard performance, perform load testing and capacity planning, and produce operational documentation and SLAs.