Top Data & Analytics Jobs in San Francisco, CA

The Sr. Data Scientist deploys data-driven explorations and predictive models to address business challenges, conducts experiments to refine product ideas, and maintains analytics models. This role also involves technical guidance in data science techniques to generate actionable insights and enhance the firm's analytics capabilities.

The Operational Risk Analyst will assist in identifying, assessing, and mitigating operational risks within the organization. Responsibilities include coordinating risk activities, conducting risk assessments, preparing governance reports, and maintaining relationships with stakeholders.

The Principal Data Privacy Consultant will assess compliance with data privacy regulations, develop privacy policies and documentation, conduct gap and maturity assessments, and provide advisory services to clients. This role involves mentoring colleagues and contributing to the growth of the data privacy consulting practice.

As a Data Scientist on the Growth team at Wave, you will design, run, and analyze experiments to enhance product features and customer experiences. The role involves working closely with operations and product teams to generate insights from data, applying statistical modeling and machine learning, and communicating findings to stakeholders.

The Lead IT Data Scientist will design and develop scalable AI and machine learning solutions, conduct research, and utilize big data tools to enhance health outcomes. Responsibilities include leading model development, data analysis for business decisions, ensuring data quality, and deploying models with CI/CD practices. The role requires collaboration with internal customers to meet AI/ML needs and communicating findings to non-technical partners.

The Principal Data Architect will lead the implementation of data practices leveraging AWS technologies, integrating Machine Learning and AI capabilities, and ensuring robust data architectures. Responsibilities include designing scalable data solutions, developing data streaming architectures, guiding data engineering teams, and collaborating with cross-functional departments to align data strategies with organizational goals.

Lead the design and development of robust data architectures that support scalable, secure, and efficient data pipelines. Drive innovation, mentor team members, ensure data quality and resilience, and collaborate with cross-functional teams to deliver impactful data solutions.