Top Senior Analysis Reporting Jobs in New Orleans, LA

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

The Senior Systems Analyst will enhance data exchanges, support project deployments, analyze data strategies, and solve complex problems within the Consumer Markets Division.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

The Senior Data Engineer will design and build scalable data platforms, handle automation for data operations, and ensure reliability and performance of data pipelines while collaborating with various teams.

Owns analytics and reporting that inform sales, merchant success, product, and fraud teams; builds business cases, pricing models, dashboards, and ROI analyses to drive merchant acquisition, expansion, and retention.

Synthesize analyses across product, marketing, reporting, and data science to create executive-ready narratives and decision materials. Partner with analytics teams and business leaders to surface high-impact insights, improve discoverability and adoption of analytics, set standards for storytelling, and ensure insights drive organizational alignment and action.

Lead analytics for member engagement and revenue recognition: build and validate Braze attributes, run attribution and A/B test analyses, maintain Looker dashboards, join campaign and engagement data via SQL/DBT, and provide actionable recommendations to Member Operations and Marketing.

Lead and grow a data engineering team, set technical standards and roadmap, architect scalable GCP data solutions (ingest, transform, warehouse, serving), ensure pipeline reliability and data quality, partner with analytics and client teams, drive best practices (CI/CD, IaC, governance), and evaluate new tooling.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Develop and optimize T-SQL scripts to transform legacy SIS data for loading into the Jenzabar platform, manage multiple conversion projects, communicate with clients and internal teams, adhere to project plans and timelines, estimate custom work, and improve conversion processes.