Data Science Jobs in Irvine, CA

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 clinical data strategy and operations across studies, owning data collection, cleaning, database lock, risk-based data review, quality monitoring, analytics, and data integrity. Partners with clinical, statistical, medical, safety, regulatory, technology, and vendor teams to support inspection readiness, patient safety, protocol compliance, and timely trial delivery. Drives process improvements, influences stakeholders without direct authority, and coaches team members.

Lead partner planning strategy for the U.S. Channel Business, aligning demand, supply, finance, and partner capabilities. Build and scale partner planning frameworks, oversee forecasting and joint business planning, drive cross-functional collaboration, KPI-driven performance management, risk mitigation, executive reporting, team development, and transformation including planning/ERP tool implementations and AI/ML enablement.

Design and optimize scalable geospatial data pipelines to convert high-frequency vehicle sensor telemetry into high-fidelity map features. Build map-matching, trajectory smoothing, and sensor-fusion algorithms, apply statistical tests for change detection and map validation, and lead system architecture for low-latency spatial indexing and storage while collaborating with embedded, perception, and cloud teams.

Lead and manage a team of data scientists to design and deliver predictive models, optimization, text analytics, and statistical analyses. Communicate model behavior and results to the business, perform technical risk and reliability assessments, design multi-model algorithms, and apply engineering approaches and data-science libraries to solve enterprise problems.