Senior AI & Data Scientist — Hybrid, End-to-End ML Systems

Charles Schwab; Austin (TX); On-site; USD 150,000 - 230,000; Full time

Job summary

Charles Schwab is seeking a Senior AI & Data Scientist to drive the design, development, and productionization of innovative AI and ML solutions at scale. You will bridge research and engineering, owning the end-to-end model lifecycle from data ingestion to monitoring.

You will collaborate across business sponsors, development teams, and engineering partners to translate strategy into practical AI applications while advancing capabilities in ML, NLP, and LLM solutions in a regulated financial

Qualifications

• 8+ years of data science and ML experience.
• Advanced degree in a quantitative field (Master’s or PhD).
• 6+ years Python and SQL in production-grade coding.
• Proven experience delivering end-to-end ML solutions across multiple lines of business.
• Experience applying NLP to unstructured data with production delivery.
• Designing LLM solutions (RAG, agent workflows, or fine-tuning) with at least one internal deployment.
• Strong software engineering fundamentals: version control, CI/CD, and MLOps with multiple productions deployments.

Responsibilities

• Get hands-on with big data to analyze, interpret, and produce AI solutions.
• Design and build end-to-end ML systems with scalable architectures for data ingestion, feature generation, model training, evaluation, deployment, and monitoring.
• Translate business strategy into technical execution with stakeholders to deliver impactful AI solutions.
• Set engineering standards for data science including modular code, testing, and production readiness.
• Lead initiatives in emerging areas like real-time inference, recommender systems, or other advanced ML technologies.

Skills

Data science

Python

SQL

Production ML

NLP

LLM systems

MLOps

CI/CD

Education

Master's or PhD in quantitative field

Job description

Charles Schwab is seeking a Senior AI & Data Scientist to drive the design, development, and productionization of innovative AI and ML solutions at scale. You will bridge research and engineering, owning the end-to-end model lifecycle from data ingestion to monitoring.

You will collaborate across business sponsors, development teams, and engineering partners to translate strategy into practical AI applications while advancing capabilities in ML, NLP, and LLM solutions in a regulated financial