Data Science Jobs in Sunnyvale, CA

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 product development for an enterprise agentic AI platform and ServiceNow catalog interpreter from concept through launch. Define product specifications, technologies, developer interfaces, user experiences, success metrics, and roadmap priorities. Partner with engineering, machine learning, design, customer success, and deployment teams; analyze product usage data; support developer ecosystems and hackathons; and build relationships with enterprise CIOs and IT leaders.

Own the Tool Studio product area for an agentic AI platform, driving development from concept through launch. Define product strategy, specifications, success metrics, developer interfaces, and end-user experiences. Partner with engineering, machine learning, design, deployment, and customers to prioritize roadmaps, improve integrations, support adoption, and build the developer ecosystem. Use product usage data, market research, and customer feedback to guide decisions while building trusted relationships with enterprise technology leaders.

Leads engineering teams delivering scalable AI and machine learning solutions on Google Cloud. Oversees generative AI architecture, Vertex AI, LangChain, LangGraph, LLM APIs, RAG, experimentation, evaluation, guardrails, and LLMOps. Guides technical strategy, client alignment, delivery execution, and team development while applying Python, data science, and machine learning methods to build reliable AI products.

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.

Configure and implement Fenergo solutions for AML and sanctions compliance, translating business and regulatory requirements into effective system configurations. Analyze complex data, apply advanced analytics and AI fluency, develop client business cases, demonstrate FenX capabilities, improve processes, engage stakeholders, and manage team members while delivering strategic consulting insights.

Leads strategy and execution for large-scale data engineering and analytics programs. Coordinates engineering, data science, product, and business stakeholders; manages roadmaps, dependencies, milestones, risks, reporting, and delivery. Ensures data definitions, transformations, models, and downstream analytics remain accurate and fit for purpose while navigating complex, ambiguous initiatives involving multiple teams and partners.

Leads pre-sales architecture and consultative selling for AI, ML, HPC, and data management solutions. Designs scalable data architectures, AI workflows, generative AI applications, and performance-optimized deployments. Conducts discovery, demonstrations, presentations, proofs of concept, and technical enablement while supporting deal closure and customer adoption. Collaborates with sales, product, engineering, marketing, hyperscalers, OEMs, and channel partners to develop joint solutions and go-to-market strategies.

Define and execute the roadmap for depot network bandwidth workflows, including software downloads and data uploads. Optimize charging and networking infrastructure, data demands, and costs by partnering with data science, engineering, networking, real estate, product, and operations teams. Drive unified strategy and effective workflow execution across depots for autonomous vehicle operations.

Leads pricing and revenue data science initiatives for consumer markets clients. Develops predictive models, forecasts trends and customer behavior, manages dashboards and visualizations, ensures data quality, and translates complex analytics into strategic decisions. Oversees client engagements, validates outcomes, directs complex projects, and coaches diverse, high-performing teams.

Own the vision, strategy, and roadmap for Microsoft Advertising’s AI-powered creative products. Lead creative automation, generative AI asset generation, quality systems, advertiser advocacy, prioritization, cross-functional execution, and go-to-market initiatives. Partner with engineering, data science, UX, marketing, sales, legal, and finance to improve creative performance, adoption, brand integrity, and responsible AI practices across advertising formats and surfaces.

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.

Leads Glean’s product design organization, managing design managers, product designers, content designers, and researchers. Establishes design standards, strategy, and vision; mentors talent; partners with Product, Engineering, Marketing, and Data Science; and drives high-quality, user-centered product experiences. The role also oversees organizational planning, hiring, team culture, cross-functional collaboration, and design execution for Glean’s AI-powered enterprise products.

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.

Owns the strategy and roadmap for Duck Creek’s billing product domain, including invoicing, payments, collections, commissions, disbursements, reconciliation, and automation. Partners with engineering, architecture, data, finance, sales, and customers to deliver configurable, scalable, compliant, and explainable billing capabilities. Leads discovery, prioritization, AI-enabled decision support, governance, adoption, and financial outcomes for insurance billing workflows.

Leads multifunctional initiatives defining safety architectures and requirements for autonomous vehicles. Develops safety concepts and analysis supporting continuous software delivery, improves safety metrics and analysis tools, evaluates safety data, and communicates readiness results. Collaborates with perception, AI, motion planning, and architecture experts to ensure DRIVE products meet rigorous safety standards.

Manage NVIDIA’s global Lenovo OEM account and drive adoption and integration of NVIDIA accelerated computing platforms. Develop technical expertise across AI hardware, networking, software, and reference architectures; identify solution opportunities; package NVIDIA technologies into Lenovo offerings; and develop co-marketing and co-selling strategies. Coordinate product, engineering, supply planning, pricing, quality, and go-to-market teams while building relationships with senior stakeholders and supporting cloud and enterprise sales channels.

Lead the Data Science function for an AI video product, setting priorities, guiding data scientists, analysts, and engineers, and solving high-impact analytical problems. Drive product, growth, experimentation, retention, monetization, and data-quality initiatives. Build reusable metrics, datasets, self-service tools, AI evaluation systems, and agentic analytics capabilities while partnering with Product, Growth, Finance, Engineering, and AI teams.

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.

Build dashboards and self-service analytics for Microsoft eCommerce, analyze customer funnels and performance drivers, investigate revenue and product trends, support experimentation, validate data quality, establish KPI standards, and communicate actionable insights to technical and business stakeholders. Use SQL, Python, Power BI, Adobe Analytics, and AI-assisted tools to improve reporting and decision-making across web, marketing, and commerce teams.

Analyze large-scale autonomous driving and simulation data to develop safety and driving-quality metrics, statistical models, predictive features, and machine-learning methodologies. Build repeatable data analysis and reporting pipelines in collaboration with engineering teams. The role requires pursuing a quantitative PhD, programming proficiency in Python or R, and strong statistical theory. Preferred qualifications include machine learning, SQL or C/C++, high-dimensional data experience, research publications, foundation-model expertise, and autonomous-driving or generative-AI internship experience.

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.

Lead causal measurement and analytics for media investments: design quasi-experimental and observational approaches, apply interpretable ML and statistics, write reproducible Python/SQL analysis, surface actionable insights for marketing partners, and uphold data ethics and stewardship.

Own AI quality for an agentic enterprise platform, including evaluation datasets, grading rubrics, regression testing, model benchmarking, cost optimization, observability, and feedback systems. Partner with engineering, product, design, sales, and client-facing teams to diagnose failures, improve prompts and models, define quality standards, and ship product changes. The role combines hands-on Python and SQL analysis with product management, LLM evaluation, RAG, document AI, and agent workflow expertise.