Top Senior Level Data & Analytics Jobs in San Francisco Bay Area, CA

As a Manager of Software Engineering specializing in Machine Learning, you will lead teams in adopting Large Language Models, mentor ML engineers, and establish best practices for implementing innovative projects aligning with the company's strategic objectives.

As a Manager of Software Engineering, you will lead and mentor a team of Machine Learning engineers, focusing on Large Language Models. Your responsibilities include driving innovation, managing processes, and overseeing the integration of ML capabilities within the organization. You will collaborate with cross-functional teams to enhance software performance and impact company goals.

The Engineering Manager will lead a team of machine learning engineers, focusing on the integration and adoption of large language models (LLMs). Responsibilities include mentoring engineers, driving process improvements, collaborating with cross-functional teams, and establishing best practices for LLM technologies.

As a Principal Data Engineer, you will design and develop BlackLine's data platform, collaborate with teams to create and optimize data models and visualization solutions, and drive innovation. You will oversee application architecture, provide technical leadership, and ensure that data-driven decisions align with organizational goals.

The Benefits Analyst will manage and ensure compliance of health and welfare benefits, insurance, and retirement programs, streamline benefits processes, resolve queries, maintain benefits platforms, assist with annual renewals, compliance reporting, and support special projects as needed.

As a Senior Manager in the PwC Intelligence team, you'll support leaders in delivering client experiences, conduct market analysis, develop service offerings, and enhance delivery capabilities. You'll address complex business challenges, manage stakeholder needs, and contribute technical expertise while fostering an inclusive environment and facilitating open communication.

As a Guidewire Data Conversion Lead and Manager, you will guide a team to resolve complex business issues, coach team members, and leverage data insights to inform decisions. You will manage data conversion processes from legacy systems, focusing on data analytics, migration performance, and business intelligence solutions.

As a Guidewire Data Conversion Lead Manager at PwC, you will solve complex business issues within financial services, focusing on emerging enterprise data management, data modeling, and analytics. You will coach team members and support development while managing a variety of viewpoints to create positive outcomes. You will also be responsible for data conversion mapping, migration performance, and building data warehouses.

The Sr Manager, Machine Learning Platform will lead the Model Engineering team at Disney, focusing on building a state-of-the-art ML runtime environment. Responsibilities include mentoring the team, providing technical direction, and partnering with stakeholders for scalable ML solutions while maintaining a culture of innovation and collaboration.

The Director of Data Science will lead a team to enhance ad performance understanding, measure ROI, and analyze audience behavior. This role involves building machine learning models, managing analytics projects, and driving data-driven insights for senior executives to improve business outcomes.

The Director of Data Science at Snap Inc will lead a team of data scientists to drive revenue growth through advanced analytics. Responsibilities include building machine learning models, improving data governance, and delivering actionable insights to senior executives. The role focuses on solving complex business questions and enhancing customer engagement using data-driven strategies.

The Staff Analyst in ITSM Problem Management is responsible for incident resolution, trend analysis, service improvements, reporting, training IT staff, and focusing on customer impact. They analyze incident data to prevent issues, optimize processes, and drive continuous improvements in problem management.