Top Data Analyst Jobs in Los Angeles, CA

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

Manage HMDA and CRA data integrity, perform validation and quality control, coordinate annual LAR and CRA submissions, resolve data discrepancies with cross-functional teams, maintain documentation and controls, support regulatory exams and audits, monitor regulatory changes, and prepare management reporting on data quality and submission readiness.

As a Principal Analyst in Growth Marketing, you will lead analytics for acquisition channels, applying advanced analytical techniques to drive business growth and improve marketing performance while collaborating across teams.

The Staff Data Analyst will lead data strategy for Compliance, analyzing regulatory engagements, and driving effectiveness through actionable insights and collaboration across various teams.

Build and maintain dbt models, write SQL to investigate and validate data, implement data quality checks, document lineage and metrics, resolve production issues (including on-call), and partner with analysts and business teams to deliver production-ready data products using modern warehouse tooling and AI-assisted frameworks.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

The Data Analyst in Digital Finance will collaborate on reporting templates, maintain analytics data, build accounting data pipelines, create dashboards, and support ad hoc data requests.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

As a Data Analyst, you'll clean and analyze survey data, use statistical software, automate procedures with programming, and communicate findings effectively.

Build and maintain HR dashboards, ensure data accuracy, develop data pipelines, analyze workforce trends (headcount, attrition, DEI, engagement), partner with leaders on hiring and retention, evaluate people programs, automate reporting, and improve HR data architecture and governance.

Support product, content, and revenue teams by building and maintaining dashboards, performing ad hoc analyses of user engagement and monetization, validating data quality, and analyzing A/B test results to translate findings into clear insights that inform product and business decisions.

Deliver analyses, dashboards, and datasets that inform GTM and Operations. Build and maintain BI dashboards, perform ad hoc analyses, enable self-serve analytics, and collaborate with data/engineering using modern data stack tools.

Maintain and validate employee data in Workday and other HR systems, run queries and reports, troubleshoot data integrity issues, support ad-hoc HR data requests, and ensure compliance with data privacy regulations to support people analytics and HR initiatives.

Serve as a brand-focused data storyteller supporting global quality, safety, and sustainability. Perform data analysis, create visualizations and dashboards (Tableau), present insights to stakeholders, mentor colleagues, propose dashboard enhancements, and manage multiple projects to drive product quality improvements. Occasional domestic travel.

The Senior Analyst will manage eDiscovery matters, collaborate with teams, develop AI tools, and ensure compliance in legal data processes.

As a Data Analyst, you'll manage certified data, develop forecasting models, define metrics, and present findings while mentoring junior analysts.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

As a Forward Deployed Data Analyst, you will configure and implement data systems for clients, ensuring their analytics are accurate and actionable. You'll work with teams to refine metrics and improve data processes, ensuring value from day one.

The Senior Marketing Data Analyst will enhance marketing performance through data analysis, optimization strategies, and collaboration with marketing stakeholders, focusing on Checking and Deposit Acquisition.

Perform data extraction from SQL/NoSQL systems, validate and transform data, and run statistical and psychometric analyses (IRT, reliability, norming). Validate assessment logic, define quality metrics, design research and simulation studies, and present findings via reports and dashboards. Collaborate cross-functionally and maintain current psychometric and data engineering practices.

Lead analytical projects, develop quantitative models, analyze datasets for insights, and translate findings into business recommendations, primarily supporting client decision-making.

Partner with GTM, Clinical Strategy, and Finance to build and maintain dbt models, client-facing reports, and dashboards. Perform SQL-based analyses, ROI and clinical outcomes reporting, and translate insights for non-technical stakeholders. Ensure data reliability through testing, code review, and collaboration with Data Engineering; support ad-hoc requests and automation of reporting.

Lead hands-on analytics role building and defining operational and clinical KPIs, performing modeling and analysis (risk, admits, LOS, financials), partnering with data warehousing to create semantic layers and a single source of truth, advising stakeholders, maintaining KPI governance and catalog, and translating clinical/business logic into actionable insights for leaders and P&L owners.