Top Remote Analysis Reporting Jobs in Santa Cruz, CA

Design, build, and operate secure, scalable cloud-native data platforms (lakehouse/data mesh) supporting batch, streaming, ML, GIS and operational workloads. Lead ingestion/transformation pipelines, distributed processing (Spark/Kafka), data governance, observability, and mentor teams while ensuring compliance in regulated environments.

Analyze conversational call flows and large datasets to optimize IVR and generative AI systems. Perform call testing, annotation, dashboard monitoring, and deliver data-driven insights and presentations to improve self-service, reduce agent handling, and enhance customer experience.

As a Senior Impact Analyst, you will analyze sustainability challenges, design and manage interventions, and work closely with smallholder communities, emphasizing rigorous research and collaboration.

The Senior Fraud Strategy Analyst will design and optimize fraud strategies, monitor performance, develop metrics, and collaborate with teams to enhance fraud detection.

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 Engineering Lead will guide a team to build a scalable AI-ready data platform, focusing on data governance, pipeline reliability, and mentoring engineers to enhance data accessibility and usability.

The Analytics Manager analyzes complex datasets, builds models, conducts scenario analyses, and provides strategic recommendations to guide decision-making for leadership.

The Principal Data Engineer will lead data architecture initiatives, design scalable data systems, and oversee data standards across teams while ensuring high-quality data infrastructure and guiding engineering teams.

Design and execute SQL-based ETL processes to migrate legacy public safety data into Mark43. Collaborate with customers, contractors, and internal teams to map legacy schemas, handle edge cases, ensure data fidelity, and improve migration tooling while managing timelines and stakeholder relationships.

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