Top Data & Analytics Jobs

Leads enterprise digital analytics strategy, reporting, KPI frameworks, experimentation analysis, data governance, and actionable business insights. Manages analytics platforms, data quality, measurement standards, and cross-functional partnerships across digital, marketing, merchandising, product, technology, and finance. Oversees hiring, workforce planning, coaching, performance management, and development of analytics professionals while presenting recommendations and influencing senior-level business decisions.

Analyzes large customer, web, firmographic, and advertising datasets to improve digital experiences and marketing outcomes. Responsibilities include defining data requirements, building automated data enablement tools and visualizations, measuring digital programs, supporting predictive models, and communicating insights to technical and non-technical stakeholders. The role collaborates across IT, marketing, sales, engineering, and analytics vendors to advance data-driven decision-making.

Analyzes aviation business data, develops reports and dashboards, identifies operational trends, supports business cases and ROI analyses, and provides insights for process improvement. The role gathers requirements, supports system implementations and user acceptance testing, collaborates with IT and vendors, monitors sales, repairs, inventory, and operations data, and communicates recommendations to stakeholders. This is an onsite position supporting GA Telesis’s Maintenance, Repair & Overhaul division.

Analyzes complex datasets to uncover business insights, develops dashboards and reports using SQL and visualization tools, and presents recommendations to stakeholders. Partners with engineering, operations, and other teams to solve business problems, prioritize strategy and projects, manage deliverables, and ensure data accuracy and timeliness.

Analyzes business processes, leasing and legal performance data, and reporting needs to identify efficiency opportunities and actionable insights. Develops AI and non-AI solution roadmaps, documents requirements, coordinates with IT and business teams, supports change management, and resolves data quality and system issues. Produces executive reports, performs ad hoc analysis, presents findings, and drives modernization across Lease Services.

Supports 24/7 grid operations by analyzing scheduling and workforce data, building Power BI and Excel dashboards, identifying trends and risks with SQL and Python, and contributing to process improvements, system migrations, training design, and monthly operations metrics. Presents findings to Control Room leadership and cross-functional stakeholders.

Business Analyst responsible for gathering, documenting, and managing business and IT system requirements. The role collaborates with Java developers and testers, leads cross-functional meetings, translates user needs into technical requirements, and ensures requirements are fully addressed. Candidates must have business analysis experience, Java and DB2 experience, HIPAA 834 transaction-set knowledge, health insurance industry experience, and a high-level understanding of PPACA legislation.

Own digital analytics, reporting, dashboard development, data extraction, ETL, and AI-enhanced insight generation for luxury e-commerce. Partner with business leaders and online retail teams to translate questions into analysis, identify trends and opportunities, improve KPIs, and create self-service reporting. Present clear recommendations to leadership, maintain data governance, validate AI-generated insights, and support data and AI initiatives.

Leads the Claims insights and analytics function, partnering with senior Claims, Reserving, Actuarial, Finance, and Underwriting stakeholders. Translates business priorities into reporting, dashboards, data products, predictive analytics, AI, and automation initiatives. Oversees delivery, measurable business value, governance, stakeholder adoption, and team development while improving claims outcomes, operational efficiency, leakage management, reserving effectiveness, and decision-making.

Build user-facing reports, data models, and pipelines in BigQuery; apply statistical analysis to generate insights; troubleshoot analytics stack issues; review schemas and code; collaborate with product and engineering teams; and use AI agents to automate workflows and surface insights. The role requires strong SQL, BigQuery, Looker, Python, data warehousing, statistics, communication, and product judgment.