AI & Data Scientist

Your opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together. 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).

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 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

The Data Scientist will work collaboratively with a team of data scientists, ML engineers, and product owners throughout a project lifecycle, including data extraction and preparation, feature engineering, model design and development and everything in between– this is a role that will requires hands on expertise to create value adding solutions that solve real business problems.

This role supports multiple business units across Schwab 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 on 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.

What you have

Required Qualifications

• MS/PHD in a quantitative field (eg. Statistics, Mathematics, Computer Science, Engineering, Physics, Operations Research, etc).
• 2+ years’ of 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
• Exposure to cloud platforms (GCP, Azure, AWS).
• 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 ie: Vertex AI, Big Query
• Experience with Bayesian statistics and marketing mix modeling
• Expertise in MLops and model monitoring
• Familiarity working in regulated environments

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