Top Data Analyst Jobs in Los Angeles, CA

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.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

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.

Supports risk portfolio programs through strategic project planning, data analysis, dashboard development, process automation, vendor and ROI management, governance, and audit documentation. The role partners with risk analysts, data scientists, Product Management, Engineering, and other stakeholders to identify risk indicators, design controls, improve workflows with AI tools, and communicate actionable insights across credit, fraud, and reputational risk initiatives.

Analyze complex data to support company-wide decisions, building metrics, scalable data pipelines, dashboards, and reports. Partner with cross-functional teams and leaders to translate business needs into data problems, deliver actionable recommendations, and improve self-service reporting. The role also involves data storytelling, stakeholder training, and enabling data literacy. Preferred experience includes Spark, Python, statistical analysis, leadership reporting, software development practices, and AI tools.

Supports database integration and maintenance, analyzes workflows and complex datasets, and develops, tests, deploys, and documents reports, dashboards, data exports, and communications. The role validates and interprets data, tracks KPIs and ROI, identifies trends, recommends improvements, and collaborates across the organization to meet reporting and business requirements.

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.

Develops Power BI dashboards, reports, queries, and ad-hoc analyses for supply chain operations and strategic decisions. Translates business needs and integrated data into actionable visualizations, enhances data integration and maturity, and identifies root causes through descriptive and prescriptive analytics. Collaborates with business, technology, analysts, and data scientists on agile product development, supports innovation, and helps junior team members succeed.

Develop Power BI dashboards, reports, and queries that translate complex supply chain data into business solutions. Partner with operations and technology teams to prioritize analytics requests, perform ad hoc analysis, identify root causes, and support strategic decisions. Use Azure Data Lake, SQL, ETL tools, and agile methodologies to improve data integration and maturity while collaborating with analysts, data scientists, and business stakeholders.

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.