Top Data Analyst Jobs in Los Angeles, CA

Owns the NetSuite item master and product data lifecycle across multiple brands. Responsibilities include managing SKUs, UPCs, attributes, BOMs, ECOs, units of measure, dangerous-goods classifications, product synchronization with WMS and Shopify, data governance, audits, and process improvements. The role partners cross-functionally with product development, operations, procurement, planning, finance, compliance, logistics, IT, and e-commerce teams to maintain accurate, scalable product data and support commercialization.

Build predictive data pipelines, machine learning models, dashboards, and automated decision tools for portfolio strategy. Analyze product performance, costs, monetization, competitive intelligence, customer behavior, and feature opportunities. Govern metrics and data quality using SQL while enabling self-service AI and natural-language data access. Support roadmap prioritization, ROI assessment, initiative tracking, and executive decision-making through advanced analytics and financial modeling.

Maintains and validates security reference and investment data across systems, investigates data-quality issues, resolves discrepancies, and strengthens operational controls. Partners with investment, technology, compliance, reporting, and external vendor teams. Supports data governance, automation, workflow improvements, vendor oversight, process enhancement, and documentation to improve data reliability and reduce operational risk.

Work independently as a healthcare analytics consultant on client projects, building strong client relationships. Use statistical tools and predictive modeling to produce business reporting and BI deliverables, perform advanced statistical analysis, create data visualizations, and operate tools such as R, SAS, SPSS, Cognos, and Business Objects. Report to the Senior Consultant.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

Analyze large datasets using SQL and Python, build dashboards and recurring reports, identify trends and data-quality issues, and translate ambiguous business questions into actionable insights. The role partners with product, customer success, and engineering teams, documents metrics and methodologies, and presents findings to technical and non-technical stakeholders. Healthcare data, supply chain analytics, modern analytics engineering, and BI visualization experience are advantageous.

Leads development and delivery of complex healthcare, clinical, provider, and financial datasets. Provides enterprise reporting, dashboards, data visualization, business intelligence, and decision support. Analyzes cost, utilization, provider, member, and clinical data to identify inefficiencies and savings opportunities. Serves as an internal analytics consultant, improves data procedures, automates reporting processes, trains team members, and ensures validation and documentation standards.

Analyze marketing and media data to measure TV and streaming campaign effectiveness, validate data and assumptions, identify actionable insights, and create clear visualizations and client-ready presentations. The analyst will use Excel, BI and data platforms, SQL, and AI tools to accelerate analysis while independently validating results and explaining methodologies, KPIs, and recommendations to internal teams and clients.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Prepare analyses for Merch & Planning, write intermediate-to-complex SQL against Snowflake, manage Tableau BI (modeling, standards, automated reports), present insights to stakeholders, partner with data engineering, and build scalable analytics solutions to inform business strategy.

Lead data analysis for product and customer decision-making by defining metrics, measuring adoption, engagement, retention, and customer health, and translating complex data into actionable insights. Partner with product, engineering, customer success, and sales teams; automate and improve data processes; support product strategy and customer reviews; strengthen data governance; and mentor analysts.

Analyze marketing data to uncover acquisition, retention, funnel, and campaign insights. Build Tableau and Looker Studio dashboards, evaluate ad spend and marketing performance, support A/B testing, integrate and validate data from platforms such as Google Ads and GA4, and provide recommendations to marketing, product, and customer experience teams. The role also improves reporting workflows and translates complex analytical findings into actionable business guidance.

The Data Analyst position requires U.S. citizenship and that all work be performed within the continental United States, Alaska, or Hawaii. The listed annual pay range is $90,000 to $110,000.

Analyzes, validates, and maintains provider data for credentialing, enrollment, health plan rosters, and regulatory submissions. The role performs data reconciliation, quality checks, reporting, exception resolution, and audit support while collaborating with credentialing, operations, compliance, contracting, enrollment, and IT teams. It also supports process improvement, automation, data governance, system testing, and documentation to improve provider data accuracy and submission timeliness.

Leads complex, cross-functional business intelligence initiatives from strategy and scoping through delivery. Partners with senior leaders across Sales, Marketing, Finance, and Operations to build scalable data products and actionable insights. Establishes standards for metrics, data modeling, governance, quality, and storytelling; designs data infrastructure using modern tools such as dbt. Drives data literacy, mentors analysts, contributes to analytics roadmaps, and ensures data assets are trusted, discoverable, secure, and fit for executive decision-making.

Lead cross-functional analytics initiatives across product, marketing, audio development, and business operations. Build data models, dashboards, self-serve reporting tools, and actionable company-wide metrics. Analyze activation funnels, A/B tests, growth KPIs, and product health while optimizing the analytics infrastructure. Partner with executives, engineering, product, marketing, and data engineering teams to improve governance, data adoption, and decision-making.

Owns roadmaps for performance marketing data products, including data ingestion, validation, analytics, and insights tools. Maintains data quality, manages technical user stories, coordinates releases, and partners with engineering, UX/UI, and external teams. The role also develops prototypes using AI and LLMs, writes SQL queries, and supports data-driven paid media campaign optimization.

Maintains roadmaps for performance marketing tools supporting paid media operations and optimization. Coordinates releases and upgrades, writes and approves technical user stories, aligns cross-functional teams, and partners with software engineers on process and tool improvements. Ensures analytics platforms, dashboards, and workflows deliver campaign value, collaborates with UX/UI teams, and prototypes tools using AI and LLMs.

Own and refine the roadmap for performance marketing tools supporting paid media optimization and operations. Write technical user stories, coordinate engineering and UX/UI teams, validate analytics platforms and data quality using SQL, Python, and Spark, automate workflows with Airtable, and develop AI- and LLM-powered prototypes. The role requires collaboration across marketing, engineering, data science, and analytics teams to improve campaign tools and processes.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

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.

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.

Conduct forensic analytics for anti-money laundering and financial crime monitoring. Analyze large transactional datasets with SQL and Alteryx, identify suspicious behaviors and emerging typologies, develop and validate detection scenarios, calibrate thresholds, perform lookbacks and segmentation studies, evaluate transaction networks, and support AML investigations, SAR narratives, and regulatory responses.

Analyze workforce data and develop HR dashboards, scorecards, KPIs, visualizations, and automated reporting solutions. Identify trends across the employee lifecycle, evaluate engagement and employee programs, ensure data quality and compliance, and provide actionable recommendations to HR and business leaders. The role also supports employee listening strategies, reporting process improvement, data governance, and executive-level presentations.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.