Top Hybrid Data & Analytics Jobs in San Francisco, CA

As a Data Scientist, your role involves building and improving models to identify credit risk, optimize marketing spending, and predict customer churn. You'll work with structured data, create classification models, and collaborate with Product and Engineering teams.

Lead a team of data scientists and engineers to develop innovative measurement products and data-driven solutions, ensure high-quality project delivery, and establish best practices for data science projects. Collaborate with multiple teams to enhance TV measurement and methodology while mentoring team members and advancing an inclusive culture.

The Disbursement Analyst manages disbursement processes and ensures timely, accurate payments while maintaining financial records. This role involves coordinating with various finance functions, managing accounts payable, assisting in audits, and preparing financial reports and analyses.

The Research Scientist will investigate fundamental questions of intelligence and knowledge to develop software with human-level intelligence. Responsibilities include creating research questions, coordinating experiments, and mentoring research engineers, while collaborating with internal and external teams.

As a Senior Data Engineer, you will design and maintain scalable data pipelines, develop data warehouse architecture, and enable advanced analytics across the organization. You will collaborate closely with software engineers to ensure data quality, create data models, implement data governance, and develop data visualization tools, all while mentoring team members and establishing best practices.

As a Data Scientist at Voleon, you will extract insights from data using machine learning techniques. Responsibilities include data analysis, interpretation, visualization, and ensuring data correctness while collaborating with the research and executive teams to enhance data-driven investment strategies.

As a Staff Data Engineer, you will drive data platform initiatives, design and optimize data architecture, and implement ETL/ELT processes for analytics and reporting, enhancing insights through machine learning and generative AI technologies.