Top Remote Data & Analytics Jobs in Raleigh, NC

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.

Build and manage HR data pipelines, ETL/ELT processes, data warehouse models, and analytics workflows across cloud platforms. Ensure data quality, governance, security, and availability for People Analytics and HR stakeholders. Lead and mentor data engineers, collaborate with business and IT teams, and support reporting and analysis using tools such as Python, R, and business intelligence platforms.

Supports applied research and evaluation projects by collecting, cleaning, managing, and analyzing quantitative and qualitative data. Conducts literature reviews and policy scans, interprets findings, prepares reports, briefs, charts, and graphs, and contributes to proposal development. Also assists with project management through timeline development, meeting coordination, and progress tracking while collaborating with interdisciplinary teams in a virtual work environment.

Analyzes customer loyalty data to generate actionable insights, recommendations, visualizations, and narratives for clients. Builds audience lists, applies segmentation and statistical modeling techniques, develops test plans, and collaborates with CRM, Data Engineering, Business Intelligence, Strategy, and Client Services teams. The role is client-facing and manages request prioritization while supporting loyalty marketing initiatives and measurable business outcomes.

Leads actuarial financial data systems and marts, developing data solutions, extracts, reports, analyses, automations, validations, and executive reporting support. Manages data mart maintenance, audits, business requirements, technical specifications, user acceptance testing, and system implementations. Provides technical leadership, coordinates vendors and departments, trains junior staff, and advises project teams on data architecture, business rules, configuration, and financial data quality.

Leads Wiley Research’s commercial analytics strategy, including KPI frameworks, executive dashboards, competitive intelligence, performance measurement, data governance, and scenario modeling. Advises executive and board-level leaders, aligns Finance and commercial reporting, consolidates fragmented data practices, and builds a trusted analytics capability across global teams. The role also develops analytical talent, drives self-service reporting, and translates complex findings into strategic decisions concerning growth, retention, investment, and market performance.

Analyzes personal lines insurance and digital product performance using SQL, BI tools, statistical methods, and financial modeling. Partners with product, experience, actuarial, finance, and operations teams to identify growth opportunities, optimize digital customer experiences, assess risks, support business cases, and influence leadership decisions. Applies AI and automation to improve analytical efficiency, communicates insights through presentations and reports, and mentors colleagues.

Lead and manage data engineering teams to design, build, and maintain high-quality data pipelines. Oversee automation, performance scripting, data modeling, database optimization, and quality-control processes. Collaborate with product, engineering, and operations to deliver data-driven features and support SEC-related data needs and AI/LLM integrations.

Lead complex BI projects to define KPIs, build internal and client-facing Tableau/Power BI dashboards, enforce documentation and metric consistency, perform data analysis and profiling, create BI strategy and roadmaps, mentor junior analysts, and present insights to cross-functional and executive stakeholders.

Build and maintain production data pipelines, transformations, governed data products, and cloud data infrastructure for a federal background investigation platform. Develop Python and SQL workflows, contribute to Terraform and CI/CD, monitor data quality and reliability, support data science and ML teams, and operate within FedRAMP, NIST 800-171, and CUI requirements. Collaborate with engineering teams, troubleshoot platform issues, and document processes in a highly regulated environment.