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Senior AI and Data Scientist

Austin, TX; Southlake, TX; Ann Arbor, MI

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Apply at Charles Schwab

What you’ll bring

All qualifications

Core experience

  • 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 two or more lines of business.
  • Proven experience developing supervised and unsupervised machine learning solutions, with delivery of three or more distinct models supported by documented evaluation metrics, performance tracking, and value measurement.
  • Experience in applying natural language processing techniques to unstructured data with at least one solution delivered to production.
  • Practical experience designing LLM solutions (such as retrieval‑augmented generation, agent workflows, or fine‑tuning), including at least one LLM system deployed for internal use.

Preferred experience

  • Experience working in financial services or other highly regulated industries.
  • Experience building, maintaining, and optimizing data pipelines that support machine learning workflows.
  • Experience developing large‑scale recommender or personalization systems.
  • 401(k) with company match and Employee stock purchase plan
Qualification wording
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 two or more lines of business.
Proven experience developing supervised and unsupervised machine learning solutions, with delivery of three or more distinct models supported by documented evaluation metrics, performance tracking, and value measurement.
Experience in applying natural language processing techniques to unstructured data with at least one solution delivered to production.
Practical experience designing LLM solutions (such as retrieval‑augmented generation, agent workflows, or fine‑tuning), including at least one LLM system deployed for internal use.
Experience working in financial services or other highly regulated industries.
Experience building, maintaining, and optimizing data pipelines that support machine learning workflows.
Experience developing large‑scale recommender or personalization systems.
401(k) with company match and Employee stock purchase plan
Education & alternatives
- 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.

Tools in this posting

  • Python
  • SQL
Source — Tool mentions in context
- 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 two or more lines of business.

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First seen by us
Jul 12, 2026 · 96d ago
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Last seen by us
Oct 15, 2026

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Job description

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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 Technology Services (STS) enables innovative and reliable technology products that power how clients manage their money, supporting Schwab’s commitment to expanding access to investing and financial planning.  Joining Schwab means joining a company committed to transforming the financial industry and putting clients at the center of everything we do.

 

We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

 

Organization / Role Description

Schwab’s AI & Data Science organization is the centralized hub for delivering responsible, production‑grade 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 compliant, resilient 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 in a highly regulated environment.

 

As a Senior AI & 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.

 

Key Responsibilities

  • Get hands-on with big data as you analyze, interpret, extract insights, and produce innovative AI solutions that enable advanced decisioning leveraging 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 two or more lines of business.
  • Proven experience developing supervised and unsupervised machine learning solutions, with delivery of three or more distinct models supported by documented evaluation metrics, performance tracking, and value measurement.
  • Experience in applying natural language processing techniques to unstructured data with at least one solution delivered to production.
  • Practical experience designing LLM solutions (such as retrieval‑augmented generation, agent workflows, or fine‑tuning), including at least one LLM system deployed for internal use.
  • Strong software engineering fundamentals, including version control, CI/CD, and MLOps practices, demonstrated through three or more production deployments.

 

Preferred Qualifications

  • Experience working in financial services or other highly regulated industries.
  • Strong background in statistics, forecasting, or causal inference.
  • 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.
  • 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 records of performance.

In addition to the salary range, this role is also eligible for bonus or incentive opportunities.


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. Our 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

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

Complete your application on www.schwabjobs.com. The employer’s form will show what is required.

Already applied? Track this application

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Pay

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Location & working pattern

Austin, TX; Southlake, TX; Ann Arbor, MI

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 Technology Services (STS) enables innovative and reliable technology products that power how clients manage their money, supporting Schwab’s commitment to expanding access to investing and financial planning. Joining Schwab means joining a company committed to transforming the financial industry and putting clients at the center of everything we do. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s). Organization / Role Description
More source context
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. Our 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:
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