Data Science Jobs in Santa Clara, CA

The role involves leading a team to build AI-enabled data features, leveraging machine learning, analyzing large datasets, and collaborating across teams to drive product innovation.

As a Senior Manager of Data Science, you'll lead the LLM Customization Team by collaborating with cross-functional teams to develop AI-powered financial solutions. You'll leverage NLP and LLMs, optimize model training, and translate technical findings for business impact.

Lead the strategy and execution of AI-driven shopping experiences, focusing on agentic AI. Collaborate cross-functionally to enhance user experiences and leverage AI technology for business growth.

The Sr. Staff Software Engineer, Automation will develop tools for automating reliability testing and analysis, collaborating with various teams to optimize workflows and improve product reliability.

Manage the operational activities of the AI Center of Excellence, lead AI initiatives delivery, oversee governance, and ensure responsible AI practices.

Oversee strategic direction of machine learning projects, collaborate with teams, develop models, ensure data quality, and mentor staff.

The Foundry Lead Engineer will manage GaN/SiC process development, oversee foundry operations, improve product quality, and collaborate with cross-functional teams while ensuring effective outsourcing strategies.

Manage external partnerships for business development in semiconductor industry, guide processes, oversee program management, and communicate with strategic partners.

Lead Safety Architect for autonomous vehicles, focusing on safety architecture, metrics, analysis, and collaborative processes for software delivery and safety standards.

Lead Applied AI product initiatives for mobile games by identifying gameplay opportunities, defining AI-driven roadmaps, translating between game design and ML teams, setting mixed technical and game success metrics, and partnering with central tech teams to deploy ML features that improve fun and retention.

Lead operations analytics across NVIDIA's ODM ecosystem, develop data-driven models, implement governance frameworks, and ensure efficient collaboration for AI supply chain enhancement.

The AI Program Manager leads AI/ML program initiatives, aligning business goals with technical execution, managing cross-functional teams, and ensuring effective delivery of AI solutions.

As an Automation Engineer, you'll build automation pipelines, collaborate on experimental needs, program instrumentation, and integrate with data science, enhancing research capabilities.

The Developer Relations Manager will support AI-native startups by providing technical guidance on NVIDIA technologies, fostering partnerships, and collaborating to solve engineering challenges.

The Senior Staff Machine Learning Scientist will drive AI-driven solutions, develop ML frameworks for recommendations, and lead technical direction for personalized customer experiences.

Lead advanced analytics and AI initiatives in compliance, collaborating with data scientists and engineers, translating requirements, mentoring, and maintaining governance standards.

As a Data Science and Machine Learning Software Engineer at NetApp, you will develop algorithms for real-time personalized search and recommendation using IoT data, while working on cloud-based services and analytics.

The role involves owning data science pipelines, delivering client-facing features, driving cross-functional collaboration, and leveraging AI tools to enhance workflows, ultimately transforming retail data into actionable insights.

The role involves designing and developing data applications, working with large data sets, and requires expertise with various data processing technologies. Candidates should have strong analytical skills and experience in prototyping software applications.

The Senior Director of Risk Data Science will lead a large team of data scientists to develop advanced fraud prevention measures using AI and machine learning. This role is responsible for setting strategic vision, deploying ML models, and ensuring their performance in a high-stakes environment.

Perform data analysis, build statistical models, and manage machine learning pipelines for product experiments, focusing on large datasets.