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.

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.

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 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.

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.

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.

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.

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

Lead product strategy and roadmap for PayPal's global P2P payments. Use data-driven insights and AI/ML to optimize web and mobile user experiences, run A/B experiments, prioritize features, and manage international launches. Collaborate with engineering, design, data science, legal/privacy/compliance, and stakeholders to balance customer needs, growth, monetization, and regulatory requirements while communicating results to senior leadership.

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.

The role involves leading data science initiatives, building machine learning models, conducting experiments, and collaborating with teams to enhance customer experiences and business outcomes.

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.

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

Lead hands-on analytics and a small team to improve eBay's shipping ecosystem using advanced analytics, AI, experimentation, and predictive modeling. Build models, simulations, data pipelines, dashboards, and run A/B tests to optimize managed shipping, carrier routing, delivery performance, and label adoption. Partner with Product, Engineering, Finance, and business teams to translate insights into measurable operational and business outcomes.

Lead and grow a homeowners insurance modeling team to build by-peril loss models, demand and retention analyses, and weather/catastrophe models. Develop reusable Python/SQL tooling and implement models in an Airflow-based pipeline, partnering with Pricing, Underwriting, Claims, Product, and Data Engineering to deploy and translate insights into business recommendations.

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.

Design and analyze A/B experiments, perform deep-dive analysis on large transactional and user-behavior datasets, build automated ETL pipelines and reporting, create Tableau/Nous dashboards and automated emails, present findings to cross-functional teams, and drive data-informed product decisions.

Collaborate with cross-functional teams to analyze A/B test and product data using SQL and Python, perform EDA, monitor health metrics, build/maintain AutoETL pipelines and Tableau dashboards, resolve data quality issues, create visualizations and presentations, and support data-driven strategies.

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.

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