Top Data & Analytics Jobs in St. Louis, MO

Leads business and systems analysis for complex mortgage lifecycle initiatives, translating stakeholder needs into business, functional, data, API, integration, and nonfunctional requirements. Develops process and system models, user stories, acceptance criteria, and testing strategies; supports Agile delivery, releases, defect resolution, and post-production validation. Partners with Product, Engineering, QA, and business teams to manage dependencies, risks, and impacts across web, mobile, legacy, and integrated systems. Mentors Business Analysts and improves analysis standards and practices.

Build and lead Surescripts’ commercial analytics function, including governed Salesforce and CRM data models, KPI definitions, dashboards, forecasting, pipeline analytics, customer journey insights, automated reporting, quota modeling, and territory planning. Manage an analyst and partner with Sales, Marketing, Finance, Data, and Business Applications. Present actionable recommendations to senior leaders while improving data quality and enabling self-service analytics.

Performs business analytics and statistical modeling to identify trends, improve processes, and support decision-making. Develops advanced Excel reports, VBA automations, Power BI dashboards, and data visualizations. Collaborates with business and IT stakeholders, manages shared data in OneDrive and SharePoint, and communicates insights to nontechnical audiences while handling multiple priorities.

Analyze credit card sales and business performance using Databricks, SQL, Power BI, and related tools. Optimize lead prioritization and conversion, evaluate customer segments and markets, design A/B tests, and connect sales metrics to revenue, acquisition, and profitability. Present actionable insights and strategic recommendations to cross-functional stakeholders while supporting marketing and business strategy.

Lead development of a unified fleet knowledge model and decision-capture pipeline for autonomous data-center operations. Build data access layers across relational, telemetry, monitoring, and time-series systems; capture labeled operator decisions; negotiate data requirements with source-system owners; and own scaling considerations including vector indexing, schema evolution, retention, and analytics separation. The role requires strong infrastructure-domain modeling, PostgreSQL expertise, and experience handling time-series and event data at scale.

Lead consumer insights projects from brief development through research design, quantitative and qualitative analysis, storytelling, reporting, and client presentation. Manage client relationships, develop actionable recommendations, create surveys, oversee project plans, and coach junior team members. Serve as a strategic advisor by translating consumer and market data into business decisions.

Develop and support a scalable business intelligence and reporting platform using ClickHouse, Python ETL/ELT pipelines, advanced SQL, dimensional models, and reporting marts. Integrate data from Elasticsearch, SQL Server, APIs, and files; optimize analytical queries; build dashboards and reporting experiences; collaborate with business stakeholders; and develop AI-enabled features for natural-language querying, insights, anomaly investigation, and automated reporting intelligence.

Analyzes sales, cost, margin, pricing, rebate, supplier, and product-category data to produce management and ad hoc reports. Supports profitability modeling, market adjustments, supplier programs, distribution agreement compliance, and business trend analysis. Collaborates with Business Intelligence, Finance, Pricing, and Product Category Management teams, while maintaining reporting tools and methodologies. May mentor entry-level team members and support special projects.

Leads the data engineering function and manages a team of at least five employees. Owns enterprise data platform execution, scalable pipeline development, Medallion architecture implementation, DataOps, CI/CD, observability, reliability, stakeholder intake, and engineering standards. Partners with data architecture and application teams, mentors engineers, drives delivery, and develops future leaders.

Leads enterprise Workforce Intelligence across Customer Excellence, integrating workforce, operational, quality, customer, and service data into actionable insights. Establishes performance frameworks, executive reporting, governance, root-cause analysis, and reporting automation. Partners with Operations, Workforce Management, Finance, HR, Training, and Technology while leading a global team and driving performance improvements.