Data Science Jobs in Sunnyvale, CA

Leads a team of Product Sales Specialists responsible for product adoption, cross-sell, expansion, pipeline, and revenue outcomes. Coaches consultative selling, manages forecasting and performance, develops scalable sales plays, and partners with Account Executives, Account Managers, Product, Marketing, Operations, Data Science, and Enablement. The role also engages in strategic seller opportunities, improves product expertise across sales teams, and builds repeatable commercial motions for Square’s products.

The Group Product Manager for AV Capabilities at GM leads the strategy and roadmap for autonomy products, managing a team while collaborating cross-functionally to ensure quality delivery and innovation.

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

The Senior Product Manager for Evaluation Applications will define and implement strategies for a testing platform, ensuring cohesive workflows. This role requires strong technical leadership, stakeholder alignment, and a focus on data-driven insights for autonomous vehicle evaluation.

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

Teach undergraduate and graduate information systems and analytics courses, including course preparation, student assessment, grading, advising, and office hours. Participate in departmental, university, professional, and community service, contribute to student learning assessment, and maintain professional activity through scholarship, conferences, pedagogy, or industry practice.

The Senior Director of Engineering leads engineering strategy, mentors teams, oversees project delivery, collaborates with stakeholders, and champions best practices for operational excellence.

Lead product strategy and roadmap for threat detection content across endpoint, cloud, and related domains. Partner with research, data science, engineering, marketing, sales, and support to deliver detections, competitive analysis, go-to-market plans, and AI-enhanced defenses. Drive cross-functional collaboration to prioritize features, influence product direction, and support customers and releases.

Source and screen specialized technical and executive candidates across AI/ML research, robotics, computer vision, software, consumer electronics, and related engineering fields. Develop multi-channel sourcing strategies, build talent networks, conduct market research, analyze sourcing metrics, engage passive candidates, and partner with recruiters and hiring managers. The role also supports employer branding, diversity sourcing, candidate qualification, and recruitment process coordination.

Lead product definition and roadmap for internal web tools that surface and audit autonomous vehicle log events. Partner with engineers, data scientists, safety, and operations to translate complex AV workflows into requirements, prioritize features, improve reviewer productivity, define success metrics, and deliver scalable, reliable visualization and triage tooling.

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.

Leads technical, process, and application initiatives supporting supply chain, planning, manufacturing, quality, and service operations. Responsibilities include defining requirements and roadmaps, managing scope, risks, resources, schedules, and multiple concurrent projects; improving and reengineering business processes; coordinating engineering teams; developing business use cases; and communicating decisions and progress across cross-functional stakeholders. The role requires supply chain expertise, technical program leadership, and experience with IT applications, infrastructure, data analytics, and Agile Scrum delivery.

Lead end-to-end product development for SaMD neurodiagnostics (EEG) products. Define vision, write requirements and acceptance criteria, manage backlog and releases, integrate AI features, ensure FDA and global regulatory compliance, drive VOC and competitive analysis, and coordinate cross-functional execution from design through verification and launch.

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 a team of data scientists to enhance infrastructure through data science, focusing on capacity planning, performance optimization, and customer experience.

Join Hiring.Cafe as a Founding Machine Learning/AI Search Engineer to develop AI recommender systems and scalable infrastructure, contributing to a transformative job search engine.

Analyzes business and data requirements, converts them into machine learning and generative AI problems, integrates data from multiple sources, builds data models and dashboards, performs statistical analysis, develops predictive and AI models, and benchmarks model improvements. The role requires Python expertise, knowledge of data science and visualization tools, generative AI technologies, and relational and non-relational databases.

Lead AI strategy and initiatives for Samsung by creating growth roadmaps, identifying high-value use cases, and translating strategy into action, while fostering responsible AI practices and cross-functional collaboration.

The Sr. Solution Engineer collaborates with Sales to advance enterprise opportunities, conducting demos, workshops, and assessments to align with customer needs and position Aera's Decision Intelligence platform as a transformative solution.

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

The Director of Data Science leads data-driven initiatives, focusing on strategy, technical execution, and cross-functional collaboration to drive business impact through advanced models and teamwork.

Leads and mentors a data science team building production-grade solutions for electric grid visibility and resilience. Oversees data pipelines, curation, annotation quality, metrics, experimentation, model evaluation, and advanced analytics. Partners with engineering, product, power systems experts, executives, and external stakeholders to define strategy, communicate insights, and deliver ML-powered products using rigorous statistical and engineering practices.

The Principal Data Scientist will adapt complex statistical concepts for executive decision-making, lead communication standards within the data science organization, and represent Databricks at industry events. Responsibilities include mentoring, producing strategic insights, and advancing scientific methodologies.

Leads a global 20-person Data Science and Data Engineering organization within Search and Discovery. Oversees optimization of LLMs, ranking models, and personalization systems; leads experimentation and metrics synthesis; and partners with senior leaders to improve customer outcomes. The role requires deep expertise in statistics and machine learning, strong executive communication, and experience managing directors and global teams.