Top Senior Analysis Reporting Jobs in Boise, ID

The Business Intelligence Senior Consultant develops BI strategies, implements solutions using Ellucian tools, and supports higher education clients with technical and functional consulting.

Lead the design and implementation of algorithmic trading strategies, oversee technical infrastructures, and mentor a multidisciplinary team while managing performance analysis and risk.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Senior Statistical Programmer will program and validate datasets for clinical trials, oversee deliverables, manage projects, and ensure compliance with industry standards. Requires strong skills in SAS and R for statistical programming.

As a Data Engineer, you will develop solutions for customer-centric technology, ensuring platform integration and managing data architecture. Responsibilities include building data processes, maintaining data integrity, and collaborating cross-functionally to meet business challenges.

The Business Intelligence Analyst will analyze pharmaceutical transaction data, develop visual data models, and collaborate cross-functionally to drive insights and improvements in business strategies.

As a Senior Analytics Engineer, you'll build data pipelines and dashboards, partner with stakeholders for KPI development, and ensure data quality across the company.

The Director of Data Analytics & Business Intelligence leads analytics functions, building models and dashboards while guiding a team. Responsibilities include analytics infrastructure management, cross-functional collaboration, and driving AI/ML initiatives.

Design, build, and maintain Scala-based ETL and streaming data pipelines, APIs, and data microservices in Azure. Optimize LLM fine-tuning and RAG workflows, support DevOps/CI-CD practices, document standards, mentor engineers, and manage data ingestion frameworks for analytics and partner integrations.

Partner with Product, Design, Engineering, and Data to define KPIs and measurement for AI-powered features, guide instrumentation, design and evaluate experiments, build dbt models, create dashboards, and influence product analytics standards and long-term strategy.