Top Remote Analytics Jobs in Boise, ID

Build and maintain production data pipelines and foundations for People Analytics and AI-driven tools. Integrate HR systems (Workday, Greenhouse), design data models, ensure governance for sensitive employee data, support data science and reporting, and deliver dashboards and Streamlit apps. Optimize queries, enable LLM consumption with quality and latency controls, and collaborate cross-functionally to transition AI prototypes to production.

Lead product analytics for Guest or Host App: analyze large datasets, design and evaluate experiments, build metrics and reporting tools, apply statistical and causal methods, partner cross-functionally, present insights to stakeholders, and leverage AI to automate tasks.

Lead analytics partner to Community Support, driving data-driven roadmaps, scalable reporting and measurement, causal inference and experimentation, and improvements to agent/guest/host experiences via analytics, modeling, and stakeholder influence.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

Lead the RevOps analytics function: manage an analytics team, own revenue reporting and forecasting, build measurement frameworks, enforce data governance, partner with BI/engineering, analyze funnel and retention metrics, and embed AI/automation to improve revenue predictability and GTM performance.

Lead analytics for law firm operations by writing advanced SQL and Python/R scripts, building executive dashboards, standardizing KPIs, analyzing case lifecycle metrics, identifying bottlenecks, and delivering actionable recommendations to drive capacity planning and process improvements.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

Lead the Payments Insights Analytics team, utilizing data and AI/ML for strategy execution, operational excellence, and stakeholder communication.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Design and maintain a formal analytics data layer (AWS Glue, Athena/Presto, LookML); build data models, pipelines, and automated quality checks; investigate anomalies; document metrics and lineage; mentor analytics team members and promote best practices.

Own reconciliation and validation of client billing across internal systems, build repeatable data-quality checks and documentation, support Client Group with reporting and dashboards, investigate discrepancies, and drive process improvements and automation to reduce billing friction.

Manage client data and analytics projects to design and implement data strategies, automation, visualizations, and predictive analytics. Translate data into actionable insights, lead cross-functional stakeholder engagement, scope and monitor budgets, and develop internal tools and templates. Apply finance/CPA knowledge where relevant and deliver client-facing presentations.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Lead analytics strategy and delivery for healthcare clients: gather reporting requirements, design and build enterprise data platforms (Databricks/lakehouse), develop and validate reports (including Epic reporting), influence decentralized data teams, and provide post-implementation support and modernization.

Lead analytics and data-product initiatives for healthcare clients: gather reporting requirements, design and develop reports/products, test and validate, provide post-implementation support, and partner with stakeholders to drive adoption and measurable value.

Build and maintain BI dashboards and reports, optimize and write advanced SQL for large datasets, create analytical database objects and data models, validate data accuracy, document metric logic, and collaborate with cross-functional teams to deliver reliable, performant reporting solutions.

Senior technical and business leader who defines analytics vision and architecture, builds scalable cloud data platforms and pipelines, drives AI/ML and self-service analytics, ensures governance and HIPAA compliance, and leads a multidisciplinary analytics team to deliver executive dashboards and data products that improve physician and revenue-cycle performance.

Lead-level analyst who designs, develops, and delivers reports, dashboards, and data solutions (SQL, Power BI, SSRS, Excel). Analyzes complex healthcare, financial, and operational data, ensures data quality and ETL processes, mentors analysts, manages analytics projects, drives automation and process improvements, and presents insights to leadership and stakeholders.

Lead identification and quantification of issuance leakage across acquisition, application, approval, and funding funnels. Analyze digital customer journeys and conversion gaps, run root-cause diagnostics, design experiments, build executive dashboards, and translate findings into prioritized, quantified business recommendations partnering with Product, Marketing, Credit Risk, Operations, and Engineering.

Lead design and governance of enterprise ontologies, knowledge graph architecture, ingestion pipelines, and semantic layers. Enable semantic interoperability across data products, implement inference and reasoning, and establish standards, versioning, and data contracts to support scalable graph-driven analytics and AI augmentation.

Own product telemetry, maintain dbt models in Snowflake, support self-service reporting and NLP queries, drive product insights from user and retention data, and monitor Airbyte syncs to ensure data quality.

Lead enterprise data analytics, pipelines, BI, and data governance. Build and monitor ELT/ETL pipelines, develop executive dashboards, define data contracts and domain models, standardize integration patterns, and ensure HIPAA/SOC2-compliant data practices across affiliated entities.

Lead design and implementation of data models, write optimized SQL at scale, enable semantic layers and AI tooling, manage analytics infrastructure, build frontend data surfaces, and partner with product and engineering to structure source systems for reporting.

Hands-on business and delivery analyst who translates stakeholder needs into data integration solutions. Leads current/future-state and gap analysis, requirements, mapping, migration, testing, and delivery coordination. Partners with Operations, Finance, Compliance, and Purchasing to streamline workflows, promote data-driven decisions, and support adoption of analytics and cloud-based tools to improve operational outcomes.

The Lead, Advanced Analytics, Acquisition will analyze data, define metrics, conduct A/B tests, and collaborate with teams to drive growth and insights.