Staff Data Scientist

Charles Schwab; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

401(k) match

Employee stock purchase plan

Vacation & sabbatical

Parental leave

Tuition reimbursement

Health, dental, and vision insurance

Job summary

Schwab seeks a Staff Data Scientist to drive design, development, and deployment of innovative AI/ML solutions addressing enterprise-scale challenges. You will bridge research and robust engineering, owning end‑to‑end model lifecycles and collaborating with sponsors, dev teams, and engineering partners.

You will lead advanced analytics and ML initiatives, including real-time inference and LLM applications, with a focus on scalability, governance, and measurable business impact.

Qualifications

• 8+ years of experience in data science and machine learning.
• 6+ years of hands‑on experience using Python and SQL to develop production‑grade, modular, and optimized code.
• Proven ability to convert business requirements into technical end‑to‑end machine learning solutions delivered against roadmap milestones for multiple lines of business.
• Proven experience developing supervised and unsupervised machine learning solutions, with delivery supported by documented evaluation metrics, performance tracking, and value measurement.
• Experience in applying natural language processing techniques to unstructured data with delivery to production.
• Practical experience designing LLM solutions (such as retrieval‑augmented generation, agent workflows, or fine‑tuning), deployed for internal use.
• Strong software engineering fundamentals, including version control, CI/CD, and MLOps practices for production deployments.

Responsibilities

• Get hands‑on with big data as you analyze, interpret, extract insights, and produce innovative AI solutions that enable advanced decisioning to leverage the latest algorithms, state‑of‑the‑art techniques, and tools.
• 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, monitoring, and value measurement in production environments.
• Translate business strategy into technical execution by partnering with business stakeholders to convert high‑level business objectives into clear, actionable data science and AI solutions 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.

Skills

Data science

Machine learning

Python

SQL

NLP

LLM

MLOps

CI/CD

Version control

Data pipelines

Education

Master’s or PhD in a quantitative field

Tools

Git

CI/CD pipelines

Job description

Your opportunity

At Schwab, you will build a rewarding career while making a difference in the lives of our millions of clients. Here, innovative thinking meets creative problem solving as we work together to challenge the status quo. You'll be part of a collaborative, technology-forward environment that values curiosity, continuous learning, and thoughtful problem-solving. Schwab Data is the centralized organization that manages and enables the use of data as a strategic asset across Schwab, supporting enterprise analytics, platforms, and data-driven decision‑making. Joining Schwab means joining a company committed to transforming the financial industry and putting clients at the center of everything we do.

Schwab’s AI & Data Science organization is a centralized hub for delivering innovative production‑ready AI and machine learning solutions that drive measurable business outcomes across the firm. The team partners with Schwab business units to identify high‑impact use cases, pilot innovative analytical solutions, and transition successful models into enterprise‑level production systems. Our mission is to accelerate the adoption of AI as a strategic product capability—ensuring models are scalable, reusable, governable, and continuously delivering value.

As a Staff Data Scientist, you will play an essential part in advancing Schwab’s capabilities by driving the design, development, and implementation of innovative AI and machine learning solutions that address complex, enterprise‑scale challenges. You'll bridge advanced research and robust engineering, owning the end‑to‑end lifecycle of high‑impact models. Successful candidates will work collaboratively across the organization with our business sponsors, development teams, and engineering partners. We are seeking a subject matter expert in all things AI, primed to identify and translate advanced analytical techniques, applications, and strategies into practical production‑ready solutions.

What You’ll Do

• Get hands‑on with big data as you analyze, interpret, extract insights, and produce innovative AI solutions that enable advanced decisioning to leverage the latest algorithms, state‑of‑the‑art techniques, and tools.
• 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, monitoring, and value measurement in production environments.
• Translate business strategy into technical execution by partnering with business stakeholders to convert high‑level business objectives into clear, actionable data science and AI solutions 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.

What you have

Required Qualifications

• 8+ years of experience in data science and machine learning.
• Advanced degree (Master’s or PhD) in a quantitative field such as computer engineering, statistics, mathematics, physics, chemistry, or related discipline.
• 6+ years of hands‑on experience using Python and SQL to develop production‑grade, modular, and optimized code.
• Proven ability to convert business requirements into technical end‑to‑end machine learning solutions delivered against roadmap milestones for multiple lines of business.
• Proven experience developing supervised and unsupervised machine learning solutions, with delivery supported by documented evaluation metrics, performance tracking, and value measurement.
• Experience in applying natural language processing techniques to unstructured data with delivery to production.
• Practical experience designing LLM solutions (such as retrieval‑augmented generation, agent workflows, or fine‑tuning), deployed for internal use.
• Strong software engineering fundamentals, including version control, CI/CD, and MLOps practices for production deployments.

Preferred Qualifications

• Strong background in statistics, forecasting, or causal inference.
• Hands‑on experience architecting machine learning solutions within cloud ecosystems (GCP, AWS, Azure).
• Experience building, maintaining, and optimizing data pipelines that support machine learning workflows.
• Proven expertise in MLOps and production model monitoring.
• A demonstrated commitment to mentorship, including coaching senior data scientists or engineers and elevating team capability through feedback and code quality.
• Outstanding verbal and written communication skills with demonstrated ability to communicate effectively with all levels of the organization.
• Self‑starter with strong organizational skills, attention to detail, and desire to continually reevaluate existing products and processes.
• Comfort in a dynamic, fast‑moving environment, with a positive attitude, solid work ethic, and strong track record of performance.

What’s in it for you

At Schwab, you’re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration—so you can build the skills to make a lasting impact. Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.

We offer a competitive benefits package that takes care of the whole you—both today and in the future:

• 401(k) with company match and Employee stock purchase plan
• Paid time 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