Top Data Analyst Jobs in Los Angeles, CA

Support Film & TV Studios analytics by translating stakeholder questions into analytical frameworks, building dashboards and self-service BI, writing advanced SQL, partnering with data engineering for pipelines and data quality, delivering insights through visualization and presentations, and contributing to advanced analytics initiatives including forecasting and ML/AI use cases.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Own and maintain the Propel PLM system to ensure accurate product data, BOMs, and integrations with ERP/CRM. Configure workflows, roles, and data structures; validate product and manufacturing documentation; support cross-functional teams; lead PLM projects; drive data quality improvements, user training, and continuous system enhancements to align PLM with production and supply chain operations.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

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

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Plan and run experiments, acquire and manage laboratory and pre-clinical data, clean and analyze large datasets, report insights and maintain data integrity. Support data tools, documentation, and cross-functional collaboration with engineers and clinicians.

Manage and ensure integrity of safety data across systems; implement data governance, ETL, and validation; analyze trends and KPIs; build dashboards and reports; support incident investigations, audits, and cross-functional stakeholders to drive risk-reduction and performance improvement.

Deliver analyses, dashboards, and datasets that inform GTM and Operations. Build and maintain BI dashboards, perform ad hoc analyses, enable self-serve analytics, and collaborate with data/engineering using modern data stack tools.

As a Data Analyst, you'll clean and analyze survey data, use statistical software, automate procedures with programming, and communicate findings effectively.

Support product, content, and revenue teams by building and maintaining dashboards, performing ad hoc analyses of user engagement and monetization, validating data quality, and analyzing A/B test results to translate findings into clear insights that inform product and business decisions.

Maintain and validate employee data in Workday and other HR systems, run queries and reports, troubleshoot data integrity issues, support ad-hoc HR data requests, and ensure compliance with data privacy regulations to support people analytics and HR initiatives.

Serve as a Senior Data Analytics Consultant specializing in Dynatrace and observability to analyze digital experience data, produce dashboards and reports, advise 4–8 enterprise clients, present findings to technical and executive audiences, configure tooling, influence product roadmap, and support client enablement and account growth.

Support data collection, cleaning, and preliminary analysis. Write and run SQL queries, use statistical tools and Python, produce visualizations, document methods, troubleshoot analytics tools, and collaborate with cross-functional teams to deliver actionable insights.

The Data Strategy & Sourcing Analyst transforms product data into a strategic asset, ensuring data integrity and driving cost savings through sourcing. Responsibilities include establishing a Single Source of Truth, conducting data analysis, and collaborating with teams for financial impact. The role requires strong analytical skills, proficiency in SQL, and experience with data management tools.

Lead the translation of sales and manufacturing rules into CIS Configurator logic and maintain master data in SAP Business One. Build configurable BOMs and routings, ensure MRP/APS readiness, validate WMS integration, run UAT, perform SQL-based data modeling and root-cause analysis, and document SOPs to ensure accurate order-to-shop-floor execution and margin integrity.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

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.

Clean, transform, process, and query programmatic datasets to support educational programs. Ensure data integrity through testing, auditing, and documentation. Build dashboards, automate workflows, identify operational bottlenecks, and provide cross-functional analytical support. Participate in annual student application evaluations and collaborate with program, data, and engineering teams to drive data-driven operational improvements.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

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.

Lead analytics work across revenue, product, customer, and operations by building dashboards, conducting deep-dive analyses, defining metrics and reporting standards, validating data quality with Data Engineering, and using AI tools to automate reporting and accelerate insights. Communicate findings to technical and non-technical stakeholders and proactively surface trends and opportunities.

Own and govern supply chain master data (items, BOMs, vendors, costs, units, MRP settings). Define standards, run audits, support ERP/ planning system configuration and enhancements, train users, and support cross-functional teams on data setup and lifecycle changes.