Top Remote Analysis Reporting Jobs in Baton Rouge, LA

Sets technical direction and architectural coherence across Netflix’s Ads Data Engineering organization. The role guides cross-domain data system decisions, partners with engineering and business leaders, mentors data engineers, shapes platform-wide initiatives, and advances AI-native data engineering. Responsibilities span modern data foundations, ad-tech data flows, privacy and governance, platform migrations, scalable data products, and collaboration with Ads Platform Engineering, Data Science, and Product teams.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.

Build and maintain client-facing dashboards, embedded analytics, and reporting solutions using Power BI and related tools. Translate client needs into metrics, data models, visualizations, and insights. Validate data accuracy, support governance and privacy standards, document solutions, train users, and respond to reporting questions. Collaborate with data engineers, customer success, product, engineering, and business stakeholders while supporting AI-enabled reporting and predictive analytics for life sciences clients.

Leads the organization’s spatial data capability by defining governance, standards, quality processes, and scalable delivery methods. Connects occupancy, utilization, and workplace data to business and real estate decisions; partners with technology teams on platform implementations and modernization. Advises clients, develops playbooks and thought leadership, improves service consistency, and supports practice growth through cross-functional, global leadership.

Supports DIRECTV FOR BUSINESS through KPI analytics, financial analysis, customer segmentation, and process improvement initiatives. The intern analyzes performance drivers, commitments, projects, and customer experience impacts; synthesizes insights into data stories; documents processes; and presents findings to leaders. The role involves cross-functional virtual collaboration and requires proficiency in Excel, PowerPoint, Python, SQL, Power BI, and data visualization.

Leads enterprise strategy, architecture, delivery, governance, and operations across data, analytics, information management, automation, AI, and GenAI. Drives transformation toward governed data foundations, reusable data products, data marketplaces, self-service analytics, and responsible AI. Oversees platforms, pipelines, dashboards, automation initiatives, budgets, vendors, and senior technical teams while partnering with business, Legal, Compliance, Quality, and Security. Builds training, adoption, stewardship, and change-management programs across a global life sciences organization.

The Senior Data Analyst will deliver quantitative insights and strategic recommendations for Customer Success Commercial Operations. Responsibilities include analyzing user behavior, developing commercial models and forecasts, translating business needs into actionable analyses, communicating findings to executives, and building scalable, reproducible data assets using complex SQL and code-based workflows. The role also supports go-to-market strategy, retention initiatives, revenue planning, operational decisions, product roadmaps, and mentorship of junior analysts.

Analyze operational, payment, enrollment, survey, and field data to identify fraud risks and anomalies. Design and validate fraud-risk indicators, support investigations, improve data quality, and translate findings into actionable recommendations. Partner with Product, Data Engineering, and operational teams to develop fraud-detection tools and improve controls. Document reproducible, audit-ready analysis while communicating uncertainty and findings clearly to nontechnical stakeholders.