Top Analysis Reporting Jobs in St. Louis, MO

The Associate Director will lead AHP’s analytics and data products domain, building curated datasets, transformation pipelines, semantic models, dashboards, and automated reporting. Responsibilities include delivering client and enterprise data products, establishing reporting standards, managing production refreshes and documentation, coordinating data engineering resources, and supporting AI initiatives. The role is hands-on, client-facing, and requires technical leadership across distributed project teams.

Leads Lexia’s business analytics and data strategy function, managing analysts and overseeing data engineering alignment. Owns BI strategy, Tableau governance, data governance, self-service dashboards, AI-enabled analytics, metric definitions, and data quality. Partners with Sales, Marketing, Customer Success, executives, and analytics engineering to translate business needs into insights, KPIs, models, and actionable recommendations. Manages analytics tools and vendors while ensuring responsible, secure, and effective use of enterprise data.

Leads Bristow’s global Flight Data Monitoring program, overseeing data processing, validation, analysis, reporting, quality control, systems, change management, confidentiality, and stakeholder coordination across participating AOCs. Manages the FDM team, maintains data integrity, evaluates event effectiveness, supports approved event-set implementation, and provides safety trends, KPIs, and recommendations to operational leaders, regulators, customers, and safety groups.

Build and maintain analytics solutions for cloud technology and network infrastructure teams. Responsibilities include gathering requirements, automating reporting, developing self-service analytics, maintaining data pipelines and models, querying multiple data sources, and communicating insights through dashboards and reports. The role supports data-driven planning, capacity management, colocation, and finance decisions while collaborating with technical and business stakeholders.

Analyze customer behavior, forecasts, market share, retention, revenue growth, and operational performance. Develop analytics frameworks, use Tableau and Snowflake with cross-functional analytics teams, apply AI-enabled workflows, and communicate actionable recommendations to leadership to support staffing, prioritization, and strategic decision-making.

Analyze complex data to support business decisions across marketing, finance, product, sales, medical affairs, and customer success. Responsibilities include defining data requirements, developing and automating data pipelines, building interactive dashboards, identifying trends and process improvements, and presenting insights to executives and external partners. The role requires advanced SQL, Python, BI, visualization, and cross-functional analytics experience, with an emphasis on using AI to improve efficiency.

Designs and optimizes scalable data platforms, architectures, and production pipelines supporting AI and machine learning. Responsibilities include Databricks Lakehouse development, batch and real-time processing, data governance, security, monitoring, performance tuning, infrastructure planning, and collaboration with DevOps, MLOps, and cross-functional teams. The role serves as the AI team’s data engineering subject matter expert and ensures reliable, secure, cost-effective data solutions.

Performs account- and portfolio-level catastrophe modeling for commercial property insurance using vendor software and internal tools. Responsibilities include validating property data, analyzing aggregate exposures and portfolio trends, supporting underwriters, delivering results to actuarial, reinsurance, and finance teams, maintaining quality controls, and developing reports and training materials. The role requires strong quantitative analysis, insurance knowledge, advanced Excel and SQL skills, and effective stakeholder communication.

The Director of Data owns the company’s data platform, governed metrics, client identity resolution, data quality, privacy controls, and AI-ready datasets. This leader manages the data team, establishes governance and operating standards, oversees warehouse and pipeline architecture, and ensures reliable data for Finance, leadership, products, and ML/LLM systems. The role requires hands-on technical leadership, roadmap ownership, stakeholder communication, and accountability for data reliability, lineage, security, and platform costs.

Lead the architecture and hands-on development of an AI-enabled data migration platform for legal software. Own extraction, transformation, orchestration, data quality, observability, and scalable go-live workflows. Partner with product management to define roadmap priorities, lead a focused engineering team, make architectural decisions, contribute code, and apply AI to migration assessment, mapping, validation, and automation.