Top Senior Level Data & Analytics Jobs

As an Analytics Manager at GoFundMe, you will lead a growing team of data analysts, spearhead the Business Intelligence initiative, develop scalable reporting systems, enforce data governance processes, optimize workflows, and collaborate with stakeholders to implement impactful BI solutions.

The ServiceNow Business Process Consultant will guide clients in adopting ServiceNow best practices, conduct needs analysis, lead business process re-engineering, and provide support and mentoring to the team. They will build relationships with clients, establish project specifications, and manage process requirements to ensure successful delivery of solutions.

The HR Data Operations Manager will oversee HR data integrity, security, and operational quality. This role includes developing HR data standards, ensuring compliance with data privacy laws, and maintaining data quality programs across systems.

The Plasma Diagnostic Scientist will design and implement optical spectroscopic tools, analyze plasma parameters using various diagnostic techniques, and support experimental campaigns. Responsibilities include the development of analytical routines and collaboration with scientists on diagnostic methodologies.

As a Lead Data Analyst, you will collaborate across teams to build models and dashboards, provide data insights, and support strategic decisions through comprehensive analysis and visualization.

As a Senior Data Analyst at Public, you'll lead analytics solutions from data gathering to modeling, conduct in-depth user analysis, and collaborate with cross-functional teams to drive growth through data insights. You will leverage advanced analytical techniques to measure the impact of growth initiatives and communicate findings to stakeholders.

As a Data Engineer, you will design, implement, and maintain data infrastructure and pipelines. Collaborating with various teams, you'll optimize data flow and ensure data reliability for informed decision-making. Responsibilities include building scalable data pipelines, defining technology strategies, and promoting best practices in data engineering.