Top Social Impact Data & Analytics Jobs in Los Angeles, CA

The Senior Data Scientist will lead analytics efforts, develop data models, and improve data pipelines to support Thyme Care's mission in oncology care, while collaborating with stakeholders to enhance performance metrics and reporting.

Lead a team of ~7 data scientists to deliver accurate product analytics and experimentation insights. Manage people, mentor staff, partner with product and engineering to build accessible data products, and improve measurement, reporting, and experiment practices to inform product decisions.

The Data Coordinator ensures data integrity and compliance by overseeing data management, conducting audits, providing training, and managing reporting related to program outcomes.

Serve as the primary data partner for Fundraising & Marketing: design and build source-of-truth data models in the lakehouse, create forecasts and donor cohort analyses, automate reporting and data products, support experiment design and ROI measurement, partner with engineering and Salesforce to improve data quality, and translate insights for leadership to drive fundraising strategy.

The Consultant supports public health stakeholders by transforming complex data into accessible visualizations and communication materials, while leading client engagements and advising on data strategies.

As a Senior Data Scientist, you will guide data-driven decision-making, lead experimentation, and collaborate on actionable insights to enhance product strategy and metrics.

The Manager, Analytics transforms complex data into actionable insights, manages analytics projects, and supports organizational decision-making across teams.

The role involves developing insights from data to shape strategies for eyewear and software operations, focusing on customer experience, operational efficiency, and business growth. Collaboration across functions and advanced analytics are key to identify trends and enhance the customer journey.

As a Senior Data Engineer, you will design ETLs for large customer datasets, improve integration tools, and mentor other engineers, impacting customer onboarding and data accuracy.