Top Remote Data & Analytics Jobs in Raleigh, NC

Design and build enterprise data models, ETL/ELT pipelines and high-performance PySpark jobs on Azure/Databricks. Enable ML/AI with MLflow and model serving, secure restricted-data environments using Unity Catalog and access controls, deploy AI agents, and evaluate emerging data and AI trends.

Manage analytical service operations by overseeing a team, designing software for data mining, developing statistical models, and generating insights for marketing outcomes. Provide training and mentorship to direct reports.

Lead enterprise data and analytics strategy and Information Delivery (BI, Data Engineering, Integration, Analytics, Governance). Own end-to-end data lifecycle, operationalize governance and quality, partner with business and AI/ML teams, ensure data security/privacy compliance, and build high-performing data organizations to drive business outcomes.

The Senior Analytics Engineer will build and scale the analytics foundation, transforming data for decision-making across multiple teams and ensuring data quality and automation.

The AI Financial Planning Analyst reviews and improves financial guidance from AI systems, works across teams to enhance member experiences, and ensures compliance with regulations.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

This role oversees the design and evolution of finance reporting solutions using Power BI, collaborating with global finance teams to create scalable analytics and insights.

The Staff Analyst will drive insights and strategies for Upstart's Personal Loans product, collaborating with multiple teams on data analysis and product optimization.

The Senior Business Analyst will support clinical program execution by analyzing data, creating dashboards, documentation, and assisting with program management.

The Sr. Incentives & Strategy Analyst will optimize and evaluate incentive programs, derive insights from data, and collaborate with cross-functional teams to support revenue strategies.

Lead design and implementation of shared, reusable analytics data models and pipelines. Drive standardization, governance, observability, and CI/CD for analytics; partner with Data Science, Infrastructure, and Product to certify metrics, modernize orchestration, and integrate AI-native tooling.