Top Senior Analysis Reporting Jobs in Richmond, VA

The AI Systems Analyst III evaluates AI projects for technical feasibility, maintains the AI Registry, analyzes data quality, and documents requirements for implementation.

The Senior Product & Growth Analyst will lead the analytics behind Trust & Will's growth, focusing on conversion, retention, and lifetime value analysis. Responsibilities include building predictive models, conducting experimentation, and delivering data-driven recommendations to stakeholders. The role involves collaborating across product, marketing, and growth teams, with a strong emphasis on user behavior and funnel analysis.

As an Analytics Engineer, you'll own analytics solutions from data architecture to visualization, ensuring streamlined insights for business stakeholders.

The Director of Data & Analytics Engineering will lead and build data platform teams, manage architecture and strategy for data systems, and integrate AI in workflows, ensuring reliable, agile data solutions meet business needs.

The Advanced Analytics Manager will lead analytics initiatives, transforming complex datasets into insights, collaborating across departments to inform GTM strategy and revenue planning.

The Senior Enterprise Performance Analyst will develop dashboards, analyze performance data, support decision-making, mentor junior analysts, and improve organizational performance.

The role involves analyzing regulatory requirements, gathering business needs, creating system specifications, and facilitating communication between stakeholders in the Property & Casualty insurance sector.

As a Data Engineer, you will operationalize data pipelines, support ML tasks, and provide expertise in data engineering and security architecture. You'll work with AI teams and present findings to diverse audiences.

The Data Analyst will build KPIs and dashboards in Power BI, analyze complex datasets, and provide actionable insights to stakeholders, mentoring junior analysts.

The Senior Data Engineer will design and optimize data infrastructure, build scalable data pipelines, and ensure data quality while collaborating with various teams.