Top Remote Analysis Reporting Jobs in Santa Cruz, CA

Own GTM performance analytics, KPI and target setting, reporting, forecasting, compensation planning, and performance reviews across Sales and Post-Sales. Identify anomalies and optimization opportunities involving conversion, churn, productivity, pricing, packaging, segmentation, channel economics, and customer quality. Partner with Finance and GTM leaders to develop recommendations, lead strategic initiatives, and ensure data integrity while translating analysis into actionable business decisions.

As the first in-house Data Engineer, you will own the data infrastructure, build and maintain data pipelines, and collaborate with teams to ensure quality data access and insights.

Lead a GTM Analytics team supporting Marketing, Sales, RevOps, and Customer Operations. Manage embedded analysts, establish trusted reporting and QA processes, review SQL and dashboards, guide funnel, campaign, sales, support, forecasting, segmentation, attribution, and experimentation analysis, and deliver executive recommendations. Partner with GTM leaders and data engineers, coach analysts, and develop self-service analytics, automation, governed dashboards, metric documentation, and AI-assisted workflows.

Owns RTB House’s performance media measurement strategy across products. Responsibilities include defining measurement taxonomies, evaluating attribution, incrementality, MMM, and MTA methodologies, managing third-party measurement partners, developing testing playbooks, piloting identity and measurement approaches, translating insights into market-facing messaging, and training commercial teams. The role requires hands-on performance media buying or oversight experience and strong ability to communicate measurement concepts, limitations, and results to technical, executive, and commercial audiences.

Designs and manages scalable data pipelines, contracts, transformation layers, and analytics models. The role focuses on data governance, observability, lineage, configuration validation, and collaboration with product engineering teams. It requires processing large datasets, integrating cloud and on-premises industrial technologies, and implementing streaming and message-queuing solutions, ideally in cybersecurity or industrial environments.

Lead advanced analytics for countrywide insurance product programs: build dashboards and monitoring frameworks, conduct deep-dive analyses and predictive modeling, identify systemic process and data gaps, partner with product and cross-functional teams, and influence strategic decisions to improve growth, retention, and profitability.

Own fraud detection and mitigation for ACH payments: design controls, run investigations, analyze performance (precision/recall, financial impact), and partner with Product, Data Science, Risk ML, and Engineering to operationalize risk strategies and transition to model-driven controls.

Own and evolve the data infrastructure powering identity and fraud products. Build and operate scalable ETL/ELT pipelines, ensure data quality and observability, optimize storage and access, support product squads, respond to production incidents, mentor engineers, and drive data platform innovation.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Build Sailor Health’s foundational data platform from scratch. Responsibilities include developing Snowflake and dbt pipelines integrating EHR, CRM, and communications data; creating data-powered web applications; automating clinical and billing workflows with Python; analyzing therapy transcripts and patient data using AI and machine learning; tracking clinical outcomes; and designing scalable data architectures in collaboration with clinicians, engineers, founders, and other teams.