Top Hybrid Data & Analytics Jobs in Los Angeles, CA

Analyzes large datasets to identify insights supporting mergers, acquisitions, diligence, and value creation decisions. Develops data models, dashboards, visualizations, and statistical or predictive analyses; cleanses and validates data; uses Python, SQL, Alteryx, Power BI, or Tableau; researches client and market information; documents findings; and collaborates with senior team members on project deliverables.

Own measurement strategy and performance improvement for Snap’s advertising measurement solutions. Lead experimental design, causal analytics, benchmarking, meta-analyses, governance, and scalable measurement initiatives. Advise executives and external partners, influence product roadmaps, develop thought leadership, and build analytical fluency across teams. Apply advanced statistics, SQL, AI tools, dashboarding, and data visualization to guide advertising efficacy decisions and identify innovation opportunities.

Designs and maintains data collection infrastructure, resilient pipelines, ETL/ELT processes, data warehouses, streaming architecture, BI reporting, and analytical systems. Troubleshoots technical defects, performs root-cause analysis, maintains specialized datasets, and owns end-to-end data collection, extraction, and cleansing. The role requires experience with AWS, Google Cloud, ETL tools, programming languages, NoSQL databases, and BI platforms.

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.

Lead social media measurement and analytics across paid and organic channels. Own KPI frameworks, ensure data integrity, manage dashboards and disparate data sources, and translate performance data into executive-level insights. Identify campaign trends and efficiency opportunities, recommend strategic pivots, and partner with creative, media, and strategy teams on forecasting, A/B testing, investment decisions, and stakeholder communications.

Build and operate production-grade data pipelines and products for manufacturing customers. Lead discovery, architecture, implementation, testing, deployment, documentation, and operational handoff. Model manufacturing data, ensure data quality and observability, and create reusable pipelines and analytics products. Work directly with customer data, manufacturing, IT, product, and engineering teams to solve ambiguous operational problems and deliver reliable solutions.

Provides entry-level GIS and information technology support under close supervision. Responsibilities include troubleshooting hardware, software, and GIS applications; assisting users; maintaining, validating, and processing spatial and attribute data; supporting GIS projects; conducting technical research; and creating maps, reports, and visual products.

Lead customer experience efficiency strategy through analytics, cost attribution, forecasting, and cross-functional execution. Build and own a large-scale customer experience cost data platform, connect operational and product decisions to P&L impact, identify savings and growth opportunities, and establish reliable cost and ROI reporting. Partner with Engineering, Analytics, Operations, Finance, and senior leadership to create quantitative frameworks, reconcile financial data, and guide investment decisions.

Manages information governance, risk, and compliance initiatives focused on attorney and client onboarding, offboarding, client transfers, legal holds, and electronically stored information. Coordinates data identification, collection, classification, transfer, metadata accuracy, repository tracking, security controls, and workspace access. Supports attorneys and business teams, resolves policy inquiries, develops compliance procedures and educational materials, and contributes to technology workflows, integrations, analytics, and internal controls.

Leads and develops a team of data scientists supporting Tinder’s Integrity organization. Partners with product leadership across safety, account integrity, anti-abuse, and moderation. Owns analytical strategy, experimentation, causal inference, measurement frameworks, high-stakes investigations, and executive-level recommendations. Requires hands-on expertise with complex datasets, classifier evaluation, and trust and safety or adversarial behavior domains.