Top Data & Analytics Jobs in Birmingham, AL

Lead and grow a data engineering team; define architecture and standards for ETL/ELT pipelines; hands-on design, code review, and development; ensure production reliability, monitoring, and incident response; partner with product and engineering on data roadmap.

Lead demand forecasting and performance analytics for eCommerce: build forecasting models, run scenario and promotional analyses, produce executive reporting, drive cross-functional predictive initiatives, and deliver market and competitive insights to inform planning and resource allocation.

Lead analytics for the Credit Card portfolio, partnering with Product, Engineering, Credit Risk, Fraud, and Marketing to deliver data-driven strategy. Perform ad-hoc and cohort analyses, design A/B tests, manage BI reports, drive portfolio growth and risk insights, and build scalable data solutions with Data Engineering. Influence executives through clear recommendations and leverage AI tools to accelerate analytics and self-service.

Lead catastrophe risk analytics across lines, validate and customize Cat models, collaborate with underwriting/actuarial/finance to inform pricing and portfolio strategy, build Cat modeling workflows, mentor analytics staff, support live catastrophe events, and drive R&D on emerging risks and vendor/model calibration.

Own and maintain KPI reporting pipelines and business logic, ensure data quality, diagnose KPI changes, perform deep-dive analyses, build dashboards and visualizations, architect data models and curated reporting zones, and partner with Data Engineering and product/marketing stakeholders to enable self-service analytics.

Analyze ad performance metrics (revenue, CPM, fill rates), produce regular reports, support yield and ad ops to optimize inventory across direct and programmatic channels, perform basic forecasting and scenario analysis, collaborate with cross-functional teams, and document insights and testing frameworks to improve monetization.

Lead CX research and knowledge strategy to turn qualitative and quantitative data into actionable recommendations. Manage end-to-end pilot projects, design surveys and research, synthesize insights for executives, develop scalable insight frameworks and knowledge systems, and partner with Marketing to translate findings into external thought leadership.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

The Data Engineer will develop and maintain data pipelines, perform data extraction and transformation, and support data analytics across the enterprise.