Top Data & Analytics Jobs

Supports revenue decision-making through booking trend, pacing, market, destination, offer, and promotional analysis. Maintains dashboards, reports, visualizations, and destination fill plans; monitors performance and recommends pricing, promotion, and inventory adjustments. Partners with Revenue Management, Sales, and Commercial teams to deliver accurate, actionable insights and maintain data integrity.

Analyzes data from university systems to support student success, operational efficiency, institutional reporting, and executive decision-making. Develops dashboards and reports, integrates data sources, ensures data quality, supports data warehousing and governance, and uses AI-enabled analytics for forecasting and anomaly detection. Collaborates with campus departments, trains end users, and promotes data literacy and responsible data use.

Develop and maintain Palantir Foundry data pipelines, transformations, analytical workflows, dashboards, and user-facing applications. Analyze and validate data from multiple sources, translate stakeholder requirements into solutions, troubleshoot issues, and support data modeling, testing, documentation, and deployment. Apply Python, SQL, JavaScript or TypeScript, ETL/ELT, cloud, low-code, and UX/UI practices while collaborating with technical teams and government clients.

Administer and maintain the Raiser's Edge NXT fundraising database; process data requests, queries, exports, imports, and constituent updates. Maintain data quality, coding structures, communication preferences, documentation, and integrations. Generate routine and ad hoc reports, prepare campaign data files, identify discrepancies, and support fundraising operations while meeting deadlines and maintaining accuracy.

The Data Analyst gathers, validates, and analyzes data from multiple sources to identify trends, evaluate KPIs, and generate actionable insights. They develop and maintain reports, dashboards, visualizations, and business intelligence solutions using tools such as Power BI. The role also involves partnering with stakeholders, translating business needs into analytical requirements, presenting findings to technical and non-technical audiences, documenting work, and improving reporting and analytical processes.

Leads analytics delivery across multiple clients, combining marketing data to evaluate performance, optimize investments, and inform growth decisions. Designs and implements advanced measurement approaches including attribution, incrementality testing, experimentation, and full-funnel measurement. Develops measurement frameworks, communicates insights to clients and senior stakeholders, partners with technical and marketing teams, supports new business, and mentors junior analysts.

Collect, clean, transform, analyze, and maintain fund and CRM data related to venture and growth equity. Ensure data quality, manage databases and taxonomies, conduct statistical analysis, create dashboards and reports, and track market and competitive activity. Partner with attorneys and cross-functional teams to deliver insights supporting fund practice decisions and business development.

Analyzes autonomous-vehicle data and driving scenarios to validate dataset quality, identify edge cases and coverage gaps, monitor quality metrics, and investigate anomalies. Reviews annotation batches, maintains dashboards and reports, and automates validation and testing workflows using Python, Pandas, and ClickHouse. Collaborates with product and engineering teams to improve annotation efficiency, testing processes, and data quality.

Own marketing measurement models for multiple customers, partnering with strategy managers from kickoff through model release, interpretation, enablement, and action planning. Configure and QA model inputs and outputs, manage escalations, deliver deep-dive analyses and scenario work, and support renewals and account growth. Build scalable playbooks, documentation, and AI-assisted workflows while translating complex measurement results into actionable budgeting and campaign decisions. Provide customer feedback to product, science, and engineering teams and support pre-sales and case studies.

Partners with Finance, Accounting, and internal teams to identify data sources, validate data quality, model datasets, and develop automated dashboards and reports. Translates business requirements into technical specifications, designs reporting workflows, performs DAX, Power Query, and SQL analysis, and supports process improvement and technical accounting research.