Top Data & Analytics Jobs in Los Angeles, CA

Conduct healthcare economics research and quantitative analysis using clinical, financial, claims, and operational data. Develop SQL and Python queries, statistical models, performance metrics, dashboards, visualizations, and financial reports. Apply data governance and quality practices, identify medical cost and utilization trends, and provide actionable recommendations to business and leadership stakeholders. Lead analytical projects, collaborate with partners, perform ad hoc analyses, and present findings in leadership-ready formats.

Supports data analysis projects in PwC’s Advisory practice, researching datasets, identifying patterns, integrating data, and creating dashboards and visualizations with Alteryx and Power BI. Assists with algorithm development, analytics automation, and data-driven insights for clients. The internship emphasizes learning PwC methodologies, collaborating with experienced professionals, and gaining exposure to AI, cloud platform design, and data architecture.

Build and maintain data pipelines, ingestion workflows, transformations, and data products using Python, SQL, and cloud data platforms. Test and troubleshoot systems while applying Git, software testing, and CI/CD practices. Collaborate with senior engineers and cross-functional stakeholders, use AI-assisted tools, and deliver reliable data solutions in a fast-paced startup environment.

Architects and evolves enterprise-scale batch, real-time, and event-driven data platforms and pipelines. Leads data modeling, distributed processing, data quality, governance, observability, CI/CD, security, monitoring, incident response, and cost optimization. Provides technical direction across hybrid cloud environments, mentors engineers, leads critical initiatives and code reviews, manages technical debt, evaluates new technologies, and partners with business and technical stakeholders. Participates in on-call rotations and supports distributed and offshore engineering teams.

Lead architecture and reliability of the data platform, build and harden ingestion (batch and CDC), own BigQuery+dbt transformations, establish testing/observability/governance, mentor engineers, develop Python tooling and APIs, run POCs for lakehouse/open table formats, and define AI-assisted development practices.

Design, build, and own scalable ETL/ELT pipelines, data models, and data infrastructure. Improve data quality, observability, performance, and CI/CD for data workflows. Partner with analytics, ML, software, and product teams, mentor engineers, and resolve complex data issues.

The Solutions Data Engineer will manage data integrations end-to-end, utilizing FloQast's Data Platform and Data Studio to connect source systems and transform data for reliable outputs across applications.

The Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Lead product data analytics: analyze large datasets, build models and dashboards, design and evaluate A/B tests, advise product decisions, automate analytics with AI-enabled tools, and collaborate with global R&D and product teams to deliver actionable insights.

Leads business performance analytics and reporting initiatives, developing Power BI dashboards, KPI frameworks, scorecards, forecasts, and actionable insights. Partners with business leaders to translate needs into reporting solutions, performs root-cause and trend analysis, validates data, establishes governance standards, and mentors analysts. The role combines hands-on reporting development, analytical problem-solving, performance measurement, and cross-functional initiative leadership.