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.

Maintains provider demographic, contract, location, roster, and termination data across enterprise systems. Processes updates, validates records, conducts audits, generates reports, resolves provider and claims-related discrepancies, investigates payment issues, and supports regulatory compliance, system enhancements, and process improvements. Collaborates with Claims, Credentialing, Finance, Customer Service, Network Management, and external providers to ensure accurate provider information, claims processing, payments, and provider network operations.

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.

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.

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.

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.

Supports brand and digital analytics by reviewing and tagging social media content, analyzing large datasets, preparing recurring and ad hoc reports, and developing dashboards. The role collaborates with platform partners and internal stakeholders, performs quantitative data pulls, communicates insights, and uses content management, social listening, visualization, and generative AI tools to improve reporting workflows.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Analyze raw usage, identity, license, and cost data from cloud, SaaS, and observability sources. Profile and map data to canonical schemas, design transformation and cost-allocation logic, assess application attribution, derive business taxonomies, and reconcile observed usage with vendor invoices. Contribute to FOCUS alignment, attribution precedence, shared-endpoint allocation, coverage reporting, and data quality specifications for engineering implementation.

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.

Performs data quality assurance for large datasets by validating imports, updates, transformations, and extracts. Writes SQL test queries, reviews database logic, executes test cases, identifies defects, verifies corrections, and documents testing results. Collaborates with data engineers, business analysts, project managers, and QA professionals to ensure data integrity and compliance with requirements.

Build risk data models, analyze fraud and risk trends, create Tableau dashboards and automated reports, and deliver actionable insights to Risk Operations leaders. The role manages analytics requirements and roadmaps while using SQL, dbt, Dataform, and AI tools to support fraud strategy, compliance monitoring, loss forecasting, and executive reporting.

Supports BILL’s risk organization through strategic portfolio planning, program and vendor management, process automation, AI tooling, dashboard development, governance documentation, and cross-functional coordination. The role analyzes project and risk data, tracks performance and ROI, develops control strategy recommendations, and communicates insights to stakeholders across risk, strategy, product, and engineering.

Administer and improve Workday and multi-platform HR security, including role-based access, security groups, access reviews, request approvals, audit support, governance documentation, and compliance controls. Evaluate elevated access requests, identify risks, resolve routine issues, coordinate remediation, and escalate complex decisions. Partner with HR, IT, Legal, and Compliance stakeholders to strengthen policies, processes, and least-privilege access across Workday, Peakon, UKG, Prism, and HR data platforms.

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

Analyzes user behavior, content metadata, engagement patterns, and topic relationships to support personalization, taxonomy, ontology, content strategy, and product decisions. Builds dashboards, identifies content gaps and behavioral trends, segments users, supports experimentation, and communicates actionable insights to product, editorial, ML, and personalization teams.

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Collects and validates patient-level clinical data from primary care clinics, maintains run and SPC charts, prepares recurring reports, and supports PDSA improvement cycles. Uses Excel, Google Sheets, and AI tools to clean data, synthesize feedback, identify trends, and improve workflows. Collaborates with clinic staff, project leads, and partners while ensuring data integrity, HIPAA compliance, and accurate reporting.

Collects and analyzes performance data, identifies trends, evaluates program effectiveness, and develops reports and visualizations for stakeholders. The role standardizes datasets, improves data collection and analytical methods, and supports data-driven decisions. It requires statistical analysis, data manipulation, visualization, and familiarity with machine learning and predictive analytics. The position is contingent on contract award and requires the ability to obtain and maintain an active Secret Clearance.

Analyzes complex sustainability datasets, validates calculations and metrics through QA and UAT, maintains assessment files and customer data exports, investigates data issues using SQL, and collaborates with product, engineering, and customer-facing teams. The role also supports automation, documentation, sustainability research, and reliable environmental impact reporting.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.

Own and maintain the data catalog, vendor and licensing records, dataset lineage, field definitions, and calculation documentation. Write SQL to trace, join, reconcile, and validate data; investigate discrepancies; QA derived metrics; prepare data extracts; and troubleshoot issues with engineering, offshore data teams, PMO, and customer service. Use AI tools to accelerate data work and maintain clear documentation for technical and non-technical stakeholders.

Leads stop loss claims data coordination for primary clients, identifies claimants, prepares claim-entry data, builds dashboards, presents insights to leadership, and drives continuous improvement initiatives. Requires at least three years of claims data analysis or operations experience, specific stop loss claims expertise, and a bachelor’s degree in Business or Analytics or comparable experience.