Top Data Analyst Jobs in Los Angeles, CA

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

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

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

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

Owns the NetSuite item master and product data lifecycle across multiple brands. Responsibilities include managing SKUs, UPCs, attributes, BOMs, ECOs, units of measure, dangerous-goods classifications, product synchronization with WMS and Shopify, data governance, audits, and process improvements. The role partners cross-functionally with product development, operations, procurement, planning, finance, compliance, logistics, IT, and e-commerce teams to maintain accurate, scalable product data and support commercialization.

Build predictive data pipelines, machine learning models, dashboards, and automated decision tools for portfolio strategy. Analyze product performance, costs, monetization, competitive intelligence, customer behavior, and feature opportunities. Govern metrics and data quality using SQL while enabling self-service AI and natural-language data access. Support roadmap prioritization, ROI assessment, initiative tracking, and executive decision-making through advanced analytics and financial modeling.

Work independently as a healthcare analytics consultant on client projects, building strong client relationships. Use statistical tools and predictive modeling to produce business reporting and BI deliverables, perform advanced statistical analysis, create data visualizations, and operate tools such as R, SAS, SPSS, Cognos, and Business Objects. Report to the Senior Consultant.

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.

Performs financial analysis, budgeting, forecasting, variance analysis, profitability and liquidity reporting, and financial modeling. Develops Power BI dashboards and automated Excel reports, uses SQL to validate data, identifies trends and anomalies, and supports regulatory reporting. Collaborates with Finance, Lending, Marketing, Operations, and Digital Banking to translate business needs into reporting solutions, present insights to management, improve processes, and support audits.

Prepare analyses for Merch & Planning, write intermediate-to-complex SQL against Snowflake, manage Tableau BI (modeling, standards, automated reports), present insights to stakeholders, partner with data engineering, and build scalable analytics solutions to inform business strategy.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Manage and ensure integrity of safety data across systems; implement data governance, ETL, and validation; analyze trends and KPIs; build dashboards and reports; support incident investigations, audits, and cross-functional stakeholders to drive risk-reduction and performance improvement.

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.

Design, develop, and maintain data systems, ETLs, reports, and dashboards to meet delegated and regulatory reporting for Claims and Provider Dispute Resolution. Extract, validate, and analyze data, perform root cause analysis, support dataset architecture, and present findings to stakeholders while ensuring compliance, performance measurement, and change management.

Analyze gameplay telemetry, player feedback, and research findings to identify trends and friction points. Build dashboards and reports, partner with analytics and development teams to ensure telemetry quality, translate complex data into actionable insights, and collaborate with User Research to connect quantitative and qualitative findings to inform design and production decisions.

Analyze large datasets to inform pricing and revenue decisions, build and maintain data models, perform data mining, produce reports and presentations, ensure data quality and governance, and collaborate with cross-functional teams to deliver actionable insights for senior management.

Build and maintain Rayda’s data warehouse, analytics infrastructure, data models, transformation layers, pipelines, and workflows. Integrate product, billing, and customer interaction data from multiple platforms, improve data quality and governance, and create reliable datasets and analytical models. Enable self-service analytics and collaborate with Product, Growth, Commercial, and leadership teams to uncover usage patterns, churn risks, and expansion opportunities.

Supports data collection, cleaning, validation, reporting, dashboard preparation, and basic analysis. Tracks business and product metrics, identifies trends, documents datasets and processes, responds to ad hoc requests, and helps improve data usability while collaborating with cross-functional teams.

Lead analytics and data science for long-term care insurance claims: analyze healthcare and claims data, build predictive models, perform EDA, prototype solutions, collaborate with stakeholders, and translate insights into business recommendations to improve reporting and decision-making.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Build SQL-based data models, reports, and Tableau dashboards for financial and SaaS metrics including ARR, RPO, and customer retention. Analyze and clean data, improve reporting accuracy and data quality, document metric definitions, and deliver actionable insights to Finance and Revenue Operations stakeholders. Use AI-assisted tools to improve analytics efficiency, manage work in Jira, troubleshoot data issues, and collaborate cross-functionally. Minimal travel of approximately 10% or less is required.

Supports data cleansing, quality checks, reporting, dashboards, data-source and metadata maintenance, data integrity, and normalization. Translates reporting requirements and analytical results for nontechnical audiences, handles sensitive information securely, and assists end users with reports and dashboards. Works under senior analyst guidance in a federal environment and must be able to obtain and maintain a Public Trust clearance.