Senior Data Scientist

About the role

At Schwab, you have the opportunity to do meaningful work that helps clients take control of their financial futures. 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.

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 AI 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 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.

Responsibilities

• Collaborate with data scientists, ML engineers, and product owners throughout a project lifecycle, including data extraction and preparation, feature engineering, model design and development.
• Create value-adding solutions that solve real business problems across multiple business units, from enterprise services such as Marketing to client and product groups like Investor and Advisor Services.

What You Bring

Machine Learning

• Knowledge of and experience with designing and implementing algorithms (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, K-Means clustering, etc.), and the ability to articulate their real-world advantages and drawbacks.

LLMs

• Experience with modern large language models from usage for embeddings and classification to agentic frameworks.
• Familiarity with evals and measurement frameworks.

Statistical Methodology

• Knowledge of advanced techniques and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc.).

Business Acumen

• Understanding the bigger picture for customers and the business and the know-how to probe beyond stakeholders’ stated requests to understand what is truly needed to capture and drive business value.

Requirements

• MS/PhD in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Engineering, Physics, Operations Research, etc.).
• Demonstrated professional experience in delivering production AI and data science products.
• Strong foundational knowledge of:
  • Statistics and probability
  • Machine learning fundamentals (regression, classification, clustering)
• Proficiency in Python and software engineering methodologies.
• Strong verbal and written communication skills.
• Self-starter with strong organizational skills, attention to detail, and desire to continually reevaluate existing products and processes.

Preferred Qualifications

• Experience with Dataiku and Google Cloud (e.g., Vertex AI, BigQuery).
• Expertise in MLOps and model monitoring.
• Familiarity working in regulated environments.

Skill Development Values

At Schwab, we believe growth happens through continuous learning, meaningful work, and collaboration. You will be empowered to deepen your technical expertise, explore innovative approaches, and take ownership of solutions that create measurable impact. We foster a culture that values curiosity, knowledge sharing, and professional development while providing opportunities to work alongside experienced AI, engineering, and business leaders. Our commitment to learning, collaboration, and career growth helps employees build skills that prepare them for future opportunities while making a difference today.