Top Senior Data & Analytics Jobs

Lead design and implementation of data governance architectures and tools (MDM, data quality), evaluate vendor products, ensure data security and ITAR compliance, draft standards, and guide lifecycle impact assessments and configurations.

Develop parametric cost estimates and Cost Estimating Relationships (CERs); design cost models, dashboards, and reports; perform statistical analysis on large datasets; develop algorithms and mathematical software; collect and analyze technical data; brief recommendations to leadership and engage cross-functional stakeholders.

Gather and document functional and non-functional requirements, collaborate with cross-functional teams, develop and execute test plans (UAT/integration), support production troubleshooting, and participate in Agile ceremonies and user trainings.

Lead analytics strategy and data science initiatives for global logistics. Integrate and analyze large datasets, build dashboards and ML-driven forecasts, support WMS implementations, and partner cross-functionally to improve operational efficiency and dealer visibility.

Lead deep-dive analyses into account takeover and fraud, design and implement real-time defenses, collaborate with product/engineering/data science, run incident response, and deliver actionable insights to protect users while preserving UX and core metrics.

Lead detection, investigation, and mitigation of payments fraud across cards and mobile. Build and own risk controls, metrics, reporting, and cross-functional analytics projects using SQL and BI tools to scale monitoring and partner with product, data science, and engineering.

Design, develop, and maintain forecasting and optimization models for contact forecasting, headcount planning, staffing and budget. Partner cross-functionally to produce data-driven recommendations, present to leadership, and mentor forecasting analysts.

Lead a team delivering enterprise data architecture and solutions for the Cat Helios platform. Define strategies, processes, and roadmaps; partner with product and business leaders to create scalable, reusable data products; ensure data sharing, governance, and high-quality architecture deliverables.

Lead the design and implementation of MetLife's enterprise data platforms, ensuring scalability, governance, and alignment with business objectives. Oversee data integration, platform performance, and team development while driving innovation and compliance with data regulations.

Lead and operationalize enterprise data governance programs: plan and execute roadmaps, coordinate cross-functional stewards and owners, prepare executive materials, manage intake/prioritization, drive change management, and support policy, metadata, lineage, catalog, and quality initiatives to ensure alignment with enterprise data strategy.

The Digital Ops Data Manager ensures the right data architecture for tracking and analytics integration, manages data assets, and collaborates with multiple teams.

The Business Intelligence Engineering Manager will lead an analytics team, drive insights, manage operations, and optimize data models while collaborating across departments and ensuring data quality and governance.

The Data Engineer will architect and deploy Big Data environments, manage data pipelines, and ensure data integrity across the organization.

The Internal Audit Manager leads risk-based audit strategies, oversees audit engagements, mentors teams, ensures compliance, and communicates with leadership while focusing on continuous improvement.