Principal Data Scientist

About the role

In this role, you will be part of the Schwab AI & Data Science organization operating as a high-leverage, senior individual contributor, designing and helping deliver production-ready AI and machine learning systems that address complex, enterprise scale challenges. You will leverage deep expertise in advanced model building and deployment, acting as a hands-on technical authority who directly influences and supports engineering teams across the organization.

Responsibilities

• Design and build end-to-end machine learning systems by defining scalable, reliable, and maintainable architectures that support data ingestion, feature generation, model training, evaluation, deployment, and monitoring in production environments.
• Translate business strategy into technical execution by partnering with senior leaders to convert high-level business objectives into clear, actionable data science and AI roadmaps that address critical business and technology challenges.
• Set and elevate engineering standards for data science by establishing best practices that treat data science as a rigorous engineering discipline, including modular code design, testing, version control, and production readiness.
• Advance technical capabilities in emerging areas by leading complex initiatives involving advanced machine learning, recommender systems, real-time and low-latency inference, or other evolving technologies that require deep technical expertise and comfort with ambiguity.

Qualifications

• Advanced degree (Master’s or PhD) in a quantitative field such as computer engineering, statistics, mathematics, physics, chemistry, or a related discipline.
• 10+ years of experience in data science and machine learning, including 3+ years operating as a senior-or staff-level individual contributor with significant technical ownership.
• Proven experience developing supervised and unsupervised machine learning solutions, with delivery of five or more distinct models or analytical systems supported by documented evaluation metrics and performance tracking.
• Experience applying natural language processing techniques to unstructured data, supported by two or more delivered analyses or production components.
• Strong software engineering fundamentals, including version control, CI/CD, and MLOps practices, demonstrated through three or more production deployments.
• Proven ability to convert business requirements into technical roadmaps, including ownership or co-ownership of two or more roadmaps reviewed with senior stakeholders and delivered against defined milestones.

Preferred Qualifications

• Experience working in financial services or other highly regulated industries.
• Hands-on experience architecting machine learning solutions within cloud ecosystems.
• Experience building, maintaining, and optimizing data pipelines that support machine learning workflows.
• Experience developing large-scale recommender or personalization systems.

Benefits

• 401(k) with company match and Employee stock purchase plan.
• Paid time off for vacation, volunteering, and 28-day sabbatical after every 5 years of service for eligible positions.
• Paid parental leave and family building benefits.
• Tuition reimbursement.
• Health, dental, and vision insurance.