Top Data Analyst Jobs in Los Angeles, CA

Analyzes complex datasets to uncover business insights, develops dashboards and reports using SQL and visualization tools, and presents recommendations to stakeholders. Partners with engineering, operations, and other teams to solve business problems, prioritize strategy and projects, manage deliverables, and ensure data accuracy and timeliness.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

Analyzes large datasets to identify trends, variances, and revenue opportunities; builds data models, validates data quality, and supports pricing strategies. Creates management reports and presentations, collaborates with analysts, business partners, and IT, and provides actionable recommendations for revenue performance and strategic decision-making.

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.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Analyze operational, payment, enrollment, survey, and field data to identify fraud risks and anomalies. Design and validate fraud-risk indicators, support investigations, improve data quality, and translate findings into actionable recommendations. Partner with Product, Data Engineering, and operational teams to develop fraud-detection tools and improve controls. Document reproducible, audit-ready analysis while communicating uncertainty and findings clearly to nontechnical stakeholders.

Analyze purchasing, payment, fraud prevention, and subscriber retention data to guide product and business decisions. Lead commerce experimentation, define metrics, validate randomization, build SQL analyses and data pipelines, and create Looker and Tableau dashboards. Partner with Product, Engineering, Data Science, and Business Operations teams to develop actionable recommendations, improve transactional data usability, and communicate findings through statistical analysis and executive presentations.

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.

The Data Analyst will optimize marketing funnel metrics, conduct analyses, manage dashboards, and promote data-driven decision-making within the team.

Build governed datasets and applied AI solutions for supply chain automation and pre-sales engineering. Develop forecasting, scenario modeling, optimization, benchmarking, and document intelligence workflows using Databricks, SQL, and Python. Publish reliable data products to Tableau Cloud, manage pursuit artifacts, and establish closed-loop learning by comparing design assumptions with operational outcomes. Partner with engineering, analytics, and solution design teams to improve automation proposals, estimates, and customer outcomes.

Supports a global Microsoft Dynamics 365 ERP integration strategy by configuring Finance & Operations and Customer Engagement modules, establishing legal entities, defining business requirements, and resolving system and data issues. Leads functional testing, UAT, deployment, test automation, quality assurance, and data migration validation. Collaborates with legal, finance, operations, and technical teams to improve business processes, automate workflows, close process gaps, and ensure accurate, effective ERP implementations.

Analyzes, validates, and prepares distribution data; develops dashboards, reports, and visualizations; supports warehouse management systems, labor management, configuration, testing, and continuous improvement. Partners with Distribution, IT, process teams, engineers, and vendors to provide business intelligence, troubleshoot systems, communicate data insights, and support operational and strategic decisions.

Analyzes complex business processes, data requirements, and information systems supporting the Defense Logistics Agency. Applies DoD Business Enterprise Architecture, data modeling, enterprise architecture, systems integration, and process analysis expertise to improve data quality, interoperability, modernization, and enterprise decision-making. This fully remote role requires Secret clearance and supports AMPS program initiatives.

Loads, queries, extracts, validates, and refreshes client data; prepares reports and deliverables; identifies automation and process-improvement opportunities; supports UAT, system implementations, and quality assurance testing; and collaborates with cross-functional teams. The role translates client requirements into actionable tasks and requires SQL, relational database, Oracle, Unix, data analysis, reporting, and communication skills.

As a Data Analyst, you'll drive innovation through data insights to support decision making and contribute to business growth.

As a Data Analyst, you will drive innovation and growth by transforming data into actionable insights, helping to improve decision-making and business outcomes.

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.

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.

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.

Analyze large datasets using SQL and Python, build dashboards and recurring reports, identify trends and data-quality issues, and translate ambiguous business questions into actionable insights. The role partners with product, customer success, and engineering teams, documents metrics and methodologies, and presents findings to technical and non-technical stakeholders. Healthcare data, supply chain analytics, modern analytics engineering, and BI visualization experience are advantageous.

Analyze, clean, and validate data from multiple sources; build reports, dashboards, and visualizations; identify trends and opportunities; track KPIs; investigate discrepancies; document analytical processes; and communicate actionable insights to cross-functional business and product stakeholders.

Leads development and delivery of complex healthcare, clinical, provider, and financial datasets. Provides enterprise reporting, dashboards, data visualization, business intelligence, and decision support. Analyzes cost, utilization, provider, member, and clinical data to identify inefficiencies and savings opportunities. Serves as an internal analytics consultant, improves data procedures, automates reporting processes, trains team members, and ensures validation and documentation standards.

Analyze marketing and media data to measure TV and streaming campaign effectiveness, validate data and assumptions, identify actionable insights, and create clear visualizations and client-ready presentations. The analyst will use Excel, BI and data platforms, SQL, and AI tools to accelerate analysis while independently validating results and explaining methodologies, KPIs, and recommendations to internal teams and clients.