Top Data Analyst Jobs in Los Angeles, CA

Leads logistics analytics and systems projects across transportation, warehousing, inventory, and integrated supply chain operations. Translates operational problems into process, data, and system improvements; partners with logistics, IT, finance, and external providers; develops SQL analyses, Tableau dashboards, and Python automation; manages requirements, testing, adoption, governance, and benefits tracking; and measures cost, service, productivity, inventory, and data-quality outcomes.

Analyzes logistics, inventory, fulfillment, transportation, and distribution data for an omni-channel pet product network. Develops dashboards, scorecards, and reports; identifies performance gaps and root causes; supports inventory, replenishment, capacity, and demand planning; validates ERP and WMS data; coordinates shipments with distribution centers, vendors, and carriers; and recommends process improvements to enhance delivery performance, cost efficiency, compliance, and operational effectiveness.

Analyzes operational and vehicle inspection data, builds and maintains reports, dashboards, queries, metrics, and data processes, and delivers insights to Operations and leadership. The role cleans and transforms large datasets, validates data quality, supports data science and engineering teams, develops monitoring systems, and presents trends and recommendations for business decisions. It also partners with product, dispatch, quality assurance, and technology teams on operational data and reporting needs.

Lead finance data governance, quality validation, reconciliation, SOX control execution, audit support, and finance-system integration initiatives. Define data standards, lineage, controls, and validation criteria across ERP, subledger, reporting, and interface environments. Partner with Accounting, Finance, Technology, and business teams on requirements, testing, cutover, defect resolution, change management, and post-production validation to ensure accurate, complete, traceable, and reliable financial data.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Analyze live game performance, player behavior, retention, engagement, and monetization. Build dashboards, write SQL queries, conduct A/B tests, establish telemetry and analytics practices, and communicate actionable recommendations to LiveOps, design, publishing, and executive stakeholders. Support data-driven optimization of game features, events, promotions, and in-game economies across development and post-launch stages.

Analyze and reconcile e-commerce financial data across payment processors, banks, accounting systems, and internal databases. Build revenue, expense, order, and renewal forecasts; produce P&L, unit economics, budget-versus-actual, and variance reporting; support month-end close; and investigate discrepancies. Transform Snowflake data using SQL and tools such as KNIME or dbt, define financial metrics, and create Sigma dashboards for Finance and leadership.

Analyze supply chain, marketing, brand, and customer service data for a DTC e-commerce business. Build inventory forecasting models, evaluate promotions and product launches, track customer service performance, transform Snowflake data using SQL and related tools, and develop Sigma dashboards. Partner with Supply Chain, Customer Service, Brand Marketing, and Data Engineering teams to improve forecasting, fulfillment, customer experience, and strategic decision-making.

Manages product and item master data across enterprise systems, including setup, maintenance, validation, bulk uploads, audits, and quality reviews. Investigates data issues, coordinates resolution with business and technology teams, documents requirements and procedures, supports system enhancements and testing, and identifies process improvements. The role also supports data governance, product identification standards, and cross-functional supply chain data requirements.

Provides data analysis and reporting support for the health vertical. Responsibilities include creating visualizations, automating reports and audits, analyzing web, email, and app engagement data, conducting retention and A/B testing analyses, supporting time-sensitive business requests, and developing expertise in assigned business areas. The role also evaluates how AI can improve analytical workflows and requires collaboration across project teams.

Provides data analytics consulting for enterprise clients using Dynatrace observability, digital experience monitoring, and business analytics data. Manages client relationships, performs ad hoc analysis, creates reports and dashboards, presents findings to technical and executive audiences, configures tools, trains users, and influences product improvements. The role translates complex performance and engagement data into strategies that improve digital experiences and business outcomes.

Extracts, transforms, and loads data from diverse sources; develops Power BI dashboards and reports; maintains data governance, quality, lineage, metadata, security, and retention practices; documents ETL processes, APIs, and reporting solutions; trains stakeholders; troubleshoots data pipelines; and identifies opportunities for automation and process improvement.

Supports enterprise data catalog development by profiling datasets, documenting definitions, and labeling data. Engineers and tests features improving AI and machine-learning model accuracy across business functions, and designs prompts for AI agents while evaluating response quality and failure cases.

Troubleshoot student information system integrations, configure imports, write SQL and extract scripts, perform database updates, validate data quality, investigate discrepancies, and resolve integration errors. The role also supports customers with ETL guidance and status updates while collaborating with product, engineering, and cross-functional teams.

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.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Analyzes operational data, builds and maintains reports and Power BI dashboards, develops data processes and pipelines, validates data quality, monitors KPIs, and presents insights to leadership. Partners with Operations, Quality Assurance, Dispatch, engineering, data science, and product teams to answer business questions, improve reporting, support analytical projects, and inform operational decision-making.

Provide analytics, automation, and reporting to support compliance testing and monitoring. Collect, validate, reconcile, and analyze large data populations; develop repeatable testing routines, dashboards, and automated solutions; support sampling, exception analysis, reporting, and stakeholder requests to identify trends, risks, and remediation status.

Analyze healthcare and clinical operations data to deliver actionable customer insights, physician performance reporting, care-quality dashboards, and scalable BI solutions. The role requires SQL-based data transformation, dashboard development, collaboration with clinical, product, engineering, and client-facing teams, and clear communication of findings. The analyst will also use AI tools for query generation, data cleaning, pattern recognition, and analytical summaries.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Build and validate recurring funder, district, and external reports; maintain dashboards, KPI reports, trend analyses, and ad hoc analyses. Analyze attendance, enrollment, participation, and site-level data to support program and leadership decisions. Document reporting definitions and data lineage, ensure FERPA compliance, identify data quality issues, and collaborate with program, compliance, operations, and data teams.

Develop predictive and statistical models, analyze operational and financial data, and create performance reports for AEG Presents. Extract, cleanse, and analyze data using SQL, Excel, Power BI, Python, and R. Implement models in proprietary software, define data requirements and structures, and communicate insights to technical and non-technical stakeholders across festivals, venues, touring, and other business areas.

Build and maintain business-facing analytical applications, Tableau dashboards, reports, and Cube semantic models. Develop production code in Python and JavaScript, query Amazon Redshift, manage Salesforce reporting, and implement data quality validation, governance, access controls, and row-level security. Collaborate with cross-functional stakeholders to translate business needs into reusable data products, support data-driven decisions, and deliver projects through Git-based workflows, code reviews, and CI/CD.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.

Own regulatory analytics and reporting by building audit-ready datasets, dashboards, data models, pipelines, governance controls, and compliance automations. Analyze complex financial and compliance data, support audits and risk assessments, monitor data quality, and translate regulatory requirements into reliable reporting solutions using Python, SQL, dbt, and Airflow. Partner with engineering, analysts, compliance teams, and leadership to deliver actionable insights and improve regulatory processes.