Top Senior Data & Analytics Jobs in Los Angeles, CA

Lead business intelligence initiatives supporting Snapchat’s Sales organization. Analyze data from multiple sources, identify campaign and industry trends, build dashboards and reports, deliver actionable revenue insights, and recommend optimization strategies. Partner with cross-functional teams on measurement strategies, product feedback, revenue programs, and growth initiatives. Communicate complex analyses to technical and non-technical audiences and influence business decisions through compelling data stories.

Leads data analysis and advanced analytics workstreams for clients, using statistical modeling, machine learning, data visualization, and Adobe Experience Cloud technologies to improve operations and strategic decision-making. Manages project planning, budgeting, execution, and completion while mentoring teams, maintaining data integrity and security, building Tableau and Power BI dashboards, identifying business opportunities, and integrating innovative analytics 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 Data Scientist in Finance will analyze financial data, create dashboards, collaborate on data engineering, and find improvements for the business.

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.

Analyzes autonomous-vehicle telemetry, time-series signals, incidents, software releases, and operational data to investigate safety issues and root causes. Integrates diverse data sources into analysis-ready datasets, validates data quality, applies engineering and signal-processing methods, and delivers rigorous findings for safety assurance and operational decisions. The role also develops reusable detection methods, metrics, pipelines, and analytical tooling while collaborating across engineering, operations, safety, human factors, and data teams.

Manages the design, development, validation, and delivery of standard and ad hoc reports, dashboards, and data visualizations. Integrates complex data sources, gathers requirements, identifies actionable insights, and supports leadership decision-making. Drives reporting initiatives, improves analytics processes, conducts complex research, and collaborates cross-functionally. Provides subject-matter expertise, guidance to junior employees, and team leadership while ensuring accurate, timely reporting aligned with business needs.

Own Eve’s go-to-market data models and semantic layer for governed metrics including pipeline, conversion, CAC, win rate, ARR, and bookings. Establish certification frameworks, modeling standards, documentation, alerting, and analytical application patterns across the organization. Partner with Sales, Marketing, Customer Success, and RevOps stakeholders, resolve conflicting metric definitions, enable AI-grounded data tools, review contributions, and mentor analytics engineers.

Analyze and optimize drug pricing using data-driven models, dashboards, reports, and strategic frameworks. Partner with Sales, Operations, Marketing, Finance, Product, pharmacy partners, and data teams to identify opportunities, define success metrics, improve reporting, and balance pharmacy economics with patient affordability. Serve as a trusted analytical advisor and support backend data development and query optimization.

Own analytical projects supporting revenue, profitability, and operational performance for the insurance business. Analyze funnels, campaigns, conversions, costs, and trends; build SQL queries and Looker dashboards; automate reporting with Python; define KPIs; validate data; and present actionable recommendations to stakeholders and leadership.