Top Data & Analytics Jobs

The Data QA Engineer is responsible for ensuring data quality through automated testing frameworks, SQL queries, and collaboration with analytics teams.

Lead customer-facing analytics: build dashboards, reports, and POCs that demonstrate ROI and utilization trends for healthcare provider data. Collaborate with data science and engineering on advanced models, assess and integrate new data sources, ensure data quality, and support presales and executive-facing storytelling.

The Data Analyst at PitchBook provides high-quality data analysis for private market research, utilizing Excel and SQL to deliver insights and support clients. Responsibilities include managing data requests, collaborating with research analysts, and contributing to content development for various media.

Analyze digital marketing campaigns and leverage data to inform business decisions, drive optimizations, and improve performance metrics.

Own marketing channel performance tracking, reporting, and analysis. Design and analyze experiments (A/B, incrementality), build dashboards in Looker/Tableau, support LTV and forecasting models, identify measurement gaps, and translate analysis into clear recommendations for Growth, Marketing, and Finance stakeholders.

Design, implement, and optimize marketplace risk strategies to mitigate buyer/seller/account abuse and payment fraud. Use large-scale analytics, experimentation, and partnership with Data Science and engineering to operationalize models, monitor KPIs, identify fraud trends, and balance fraud prevention with user experience. Mentor analysts and lead cross-functional initiatives to protect platform integrity.

Lead analytics across business programs, delivering insights, forecasts, dashboards, and governed datasets. Partner with Data Science, Product, and Engineering to define measurement, build pipelines, monitor model health, and produce executive-ready recommendations. Establish analytics and AI best practices, mentor analysts, and replace manual processes with automated reporting and decision analytics.

Lead enterprise technology reference data strategy and build a Databricks-based data fabric. Define governance, taxonomies, metadata, canonical models, and data products. Enable integrations, APIs, Power BI reporting, data quality controls, and observability. Partner with infrastructure, cyber, finance, risk, and engineering to deliver trusted, governed, consumable technology data for analytics, reporting, and decision-making.

The Senior Business Analyst will oversee projects, guide teams in requirement management, and ensure comprehensive business analysis within the Metal Commodities domain. Expertise in commodities, SQL, and vendor applications is essential.

Perform large-scale data acquisition and analysis to drive acquisition and engagement strategies. Integrate multiple data sources, identify trends, run statistical analyses, build actionable insights, support experimentation and performance tracking, and present findings to technical and non-technical stakeholders in partnership with growth, product, digital, and technical teams.