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.

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.

Manage product and item master data across enterprise systems, including setup, maintenance, bulk uploads, validation, audits, and data quality reviews. Investigate root causes of data issues, coordinate resolutions with business and technology teams, document requirements and processes, and support system enhancements and user acceptance testing. The role also contributes to data governance, process improvement, regulatory and industry data standards, and global supply chain initiatives.

Leads end-to-end experimentation and behavioral analysis for streaming product user experiences. Defines metrics, designs and analyzes A/B tests, conducts power analysis, studies user engagement, builds dashboards, and delivers recommendations to product managers and executive stakeholders. Uses advanced SQL and Python to analyze behavioral data at scale, with Looker and Tableau for visualization and monitoring.

Leads analytics projects evaluating Disney streaming product performance and user engagement across Hulu and Disney+. Analyzes navigation, pathing, subscriber, content, messaging, and churn data; investigates anomalies and root causes; develops optimization recommendations; partners with Product, Engineering, and Data teams; and creates Tableau and Looker dashboards and reports. Applies advanced SQL, statistical methods, Python or R, data warehousing concepts, and compelling stakeholder communication to deliver actionable insights.

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.

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.

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.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Support Items Master Data Management by collecting, cleansing, and analyzing supply chain product, contract, and pricing data. Build SQL-based reports and dashboards, ensure data quality and governance, support system implementations and migrations, and collaborate cross-functionally to drive standardization and operational improvements.

Leads advanced analytics initiatives supporting Tribal healthcare programs and strategic decision-making. Develops predictive and prescriptive models, integrates complex data sources, establishes data quality frameworks, evaluates healthcare data resources, and produces reports and dashboards. Coordinates cross-functional projects, ensures federal compliance, supports quality measurement, mentors junior staff, and may serve as a team lead.

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.

Analyzes data from internal and external sources to identify business performance trends, root causes, and improvement opportunities. Builds dashboards, visualizations, reports, and business intelligence tools for stakeholders in the fintech space. Partners with internal teams to define data needs, communicate findings, recommend operational improvements, and support the UX/UI experience of data products.

Analyzes product performance, identifies trends and opportunities, and develops reporting solutions, dashboards, and KPI tracking systems. Builds and maintains Power BI and Qlik dashboards, validates reporting logic and data quality, performs QA testing, and documents reporting processes. Collaborates with stakeholders and cross-functional teams to define requirements, deliver insights, improve reporting efficiency, and support product decisions.

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.

Leads marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Profiles and analyzes data sources, documents end-to-end lineage, maps source data to canonical models, and supports API schema design. Develops data quality, validation, metadata, and governance documentation while collaborating with engineers, architects, clients, and stakeholders to define clear technical requirements for enterprise data products, APIs, and analytics.

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.

Analyzes and integrates complex datasets to produce actionable insights, reliable management reports, and data quality improvements. The role develops SQL-based analyses, monitors and configures systems, supports information systems projects, and communicates findings to technical and nontechnical stakeholders. Candidates must work independently, solve complex data challenges, and be proficient with Microsoft SQL Server, SQL Reporting Services, Excel, Access, databases, and a scripting language.

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.

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

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.