Data Science Jobs in San Jose, CA

As a Staff Machine Learning Engineer, you will enhance credit modeling, manage full credit modeling stacks, and support innovations within regulated banking frameworks.

Ten-week, full-time paid Data Science internship (June–August 2027) working on machine learning, deep learning, and large-scale data analysis. Interns evaluate modeling tools, integrate internal and external data/APIs, design data science models, and present insights to stakeholders. In-person attendance at an assigned U.S. location is required; interns may be considered for full-time roles after graduation.

Ten-week, full-time paid Data Science internship for current PhD students. Interns will build and evaluate modeling and analytics tools, integrate internal and external data sources, design data science models, and communicate results. Candidates must continue their PhD after the internship and may be evaluated for full-time roles upon graduation.

Lead development of next-generation entity resolution ML solutions using transformers, graph ML, and large-scale data pipelines. Partner with cross-functional teams to design, train, validate, and deploy models on cloud platforms, leverage agentic AI workflows, and translate technical work into business outcomes.

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

As a Manager in Data Science, you'll lead the development of machine learning models, partner with engineering and product teams, and analyze large datasets to enhance customer experiences and prevent fraud.

Lead product strategy and lifecycle for local AI system software, tools, and apps. Drive customer discovery, define requirements, coordinate cross-functional teams, set KPIs, and support go-to-market to increase adoption of local AI solutions.

The Product Development Engineer drives testability and manufacturability of circuits, performs yield analysis using data science techniques, and interfaces with various engineering teams to optimize silicon yield and quality.

As a founding Data Scientist/Machine Learning Engineer, you'll develop AI/ML models, enhance product capability, and drive impactful user outcomes while working closely with product teams.

Lead and grow a Data Science team for Provider Products, set analytical direction, own experimentation and measurement, review methods, partner with product and engineering, hire and develop data scientists, standardize analytics and integrate generative AI to improve workflows and outputs.

Lead and build a greenfield marketing measurement function across B2C and B2B. Own attribution, incrementality, MMM, MTA, LTV, and experimentation; hire and mentor data scientists; partner with marketing leadership to turn statistical results into investment decisions; integrate measurement with data platform and GenAI tools.

Manage and grow NVIDIA's networking business with Oracle by identifying opportunities, qualifying solutions with engineering and PM teams, driving forecasting and NPI, acting as the customer advocate, and supporting deployment of networking products in cloud and data centers.

Lead a team to deliver AI powered products, leveraging machine learning and NLP for customer applications, while collaborating with cross-functional teams.

The role involves leading a team to develop AI and ML solutions, manage customer interactions, and analyze large data sets using various technologies.

Lead research and development of emerging ML (embeddings, foundation models, transformers). Build and productionize machine learning models at scale, partner with product and engineering, analyze large-scale transactional and clickstream data, and run experiments to improve customer experiences across marketing, servicing, and fraud domains.

Own strategy and roadmap for content conversion across Roku, drive conversion metrics, optimize supporting media and watch options, lead end-to-end A/B experimentation, identify and close conversion gaps with qualitative and quantitative signals, and collaborate with engineering, design, data science, and monetization while communicating progress and trade-offs to leadership.

The Engineering Leader will oversee software and data teams, ensuring product delivery and operational excellence in robotics and IoT systems.

Lead cross-functional planning and execution for the IR Data Product team, managing schedules, risks, dependencies, releases, and resource planning for data processing pipelines. Coordinate software, hardware, science, and product teams; provide reporting, process improvements, and ensure delivery readiness in a hybrid San Jose environment.

Lead the strategy for AI analytics products, building AI-powered workflows for performance diagnostics and insights. Collaborate with teams to enhance data-driven decision-making and product health monitoring.

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.

Lead CRM analytics to drive personalization, experimentation, and measurement. Define metrics and frameworks, partner on ML/AI models, run rigorous A/B and causal tests, build scalable data pipelines and self-service reporting, and translate insights to influence product and marketing strategies.

Lead global product strategy and lifecycle for large-scale network orchestration, telemetry, and analytics products. Define technical use cases and architecture requirements, guide cross-functional teams, engage customers and partners, and deliver scalable datacenter networking solutions aligned with NVIDIAs AI infrastructure roadmap.

Lead product strategy, roadmap, and execution for Hippo Plus across underwriting, claims, service, policy management and CX. Build AI-native features, partner with engineering and business teams, and drive growth, efficiency, launches, and continuous improvement.

Design and maintain scalable data pipelines and unified data models for marketing measurement. Build BI dashboards, reporting frameworks, and semantic layers. Implement data governance, quality checks, and anomaly detection. Perform measurement, attribution, forecasting, and audience segmentation. Support AI-enabled and conversational analytics, generate automated insights, and present findings to stakeholders.

As a Senior Manager of Data Science and Analytics, you will lead a team, drive strategic insights, define metrics, and ensure data-driven decision-making within eBay Live’s Trust & Safety initiatives.