Top Analysis Reporting Jobs in Boise, ID

Lead analyses to improve conversion and efficiency across the mortgage origination funnel; define success metrics, partner with Sales, Operations, Product and Engineering, produce actionable insights, and shape the analytics roadmap.

Lead measurement and data foundations translating contact center and customer feedback into quantified opportunities. Define metrics, partner with Data Engineering to build scalable data models, validate instrumentation, run impact analyses, and deliver executive-ready insights to inform product and CX prioritization and reduce cost-to-serve.

Own lightweight data governance and operational reporting: define/document business terms, maintain a data catalog, build SQL-based operational datasets and reports, monitor data quality, diagnose anomalies, and align stakeholders across BizTech, Analytics, and business teams.

The Sr Principal Analyst will conduct in-depth research, analyze market trends, and provide actionable insights to clients, enhancing their decision-making and performance. This role involves client engagement, presenting findings, and collaborating within a research community.

The Director Analyst will produce actionable research in talent management technology, mentor team members, and engage with C-level executives to enhance decision-making and strategy.

The Director Analyst will oversee the procure to pay lifecycle, master data management, and procurement data analytics, ensuring integrity and optimizing operations.

Lead advanced analytics for the Host App, performing complex quantitative analysis, experimentation, causal inference, metric design, and reporting. Partner with cross-functional teams to drive product decisions, build data pipelines and analytical tools, and present insights to senior leadership to optimize host and guest experiences.

Build and maintain cloud data pipelines and ML feature/model workflows in Snowflake and AWS. Implement data ingestion, transformations, quality checks, monitoring, and documentation. Collaborate with data scientists, analysts, and product teams to support analytics, audience insights, rapid prototyping, and reliable production deployments.

Hands-on technical lead designing and delivering secure, scalable Azure analytics solutions. Lead solution architecture, guide implementation, mentor engineers, advise on Power BI architecture and governance, and support delivery, consulting, and reuseable asset creation.

Lead enterprise Power BI architecture and governance, design scalable semantic models and high-performance reports, enable self-service analytics, optimize large-dataset performance, and mentor analytics teams while aligning solutions with business requirements and data engineering.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Drive marketing performance measurement and attribution by building dashboards, standardizing campaign tracking across HubSpot and Salesforce, running funnel and cohort analyses, ensuring data integrity, and delivering executive reporting to connect marketing activity to pipeline and revenue.

Design, develop, and optimize Tableau dashboards and data sources on Redshift; collaborate with data engineering (dbt) and business teams; own Tableau governance, performance tuning, documentation, training, and ensure data security compliance.

Design and maintain ELT pipelines, build dimensional (star/snowflake) analytics models, implement data transformations and quality checks, document data lineage and governance, partner with BI users, and mentor junior engineers to deliver performant analytics for business reporting and KPIs.

Design, build, and scale data pipelines and integrations for the TDX platform. Implement REST API integrations, ingest and unify customer data, optimize pipelines for performance and quality, ensure data security and governance, and collaborate with Product, Data Science, and customer teams to deliver reliable analytics-ready data.