Top Remote Data & Analytics Jobs in Santa Cruz, CA

Analyze user behavior, feature adoption, and retention across a B2B SaaS platform to generate evidence-based product insights. Track journeys, run cohort and funnel analyses, support A/B testing, define product KPIs, ensure data accuracy, and provide structured recommendations to inform roadmap and improve adoption and retention.

Own end-to-end analysis of payments, chargebacks, and user lifecycle to identify drivers of net loss. Deep-dive into fraud cases, design and evaluate A/B experiments and risk-rule changes, build monitoring dashboards, partner with Risk, Payments, and Product to convert insights into mitigations, and run ad-hoc analyses of emerging loss trends.

Lead architecture and evolution of Cardlytics' AWS-based data compute platform and lakehouse. Define standards for batch, streaming, ML, and AI workloads; build semantic layer, feature store, and governance. Partner with analysts and engineers, drive CI/CD (Terraform, GitHub Actions), monitoring, security, cost governance, and incident response while mentoring teams and shaping platform strategy.

Lead and own the population health analytics pipeline: intake and reconciliation of claims, eligibility, and MAO-004 data; identify and reconcile care gaps and closures; deliver practice-level performance analysis and billing reconciliations; build funnel instrumentation; document, standardize, and automate pipelines with Product and Engineering. Ensure billing-grade accuracy and support program measurement aligned to CMS reconciliation windows.

Design, build, and maintain scalable batch and streaming data pipelines, improve data modeling and governance, contribute to enterprise data architecture, and collaborate with cross-functional teams to ensure reliable, high-quality data for analytics and operational use.

Own portfolio monitoring and forecasting across card and loan products. Build executive dashboards and forecasting frameworks, perform RCA and remediation, support loss forecasting and provisioning, and collaborate with Risk, Finance, Capital Management, Engineering, and Accounting to inform strategy and lender negotiations.

Build and maintain production-grade data processing systems and foundational infrastructure for enterprise AI. Collaborate with researchers and engineers, deliver end-to-end implementations, transform unstructured data into performant datasets, and use distributed processing frameworks and modern analytics tooling to inform products and strategy.

The Actuarial Specialist produces analyses, manages projects, and oversees team workload to enhance actuarial processes in the organization, ensuring business growth and profitability.

The Data & Analytics Architect will design and implement analytics solutions, support client engagements, and lead data architecture projects, requiring extensive technical and consulting skills.

As a Machine Learning Engineer, you'll develop and deploy ML models for medical imaging, collaborate with teams, and optimize for production environments.