AI & Data Scientist

Charles Schwab Inc.•Austin, TX

2d•$100,000 - $140,000•Onsite

About The Position

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.

Requirements

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
Strong foundational knowledge of 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.
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.
Experience with modern large language models from usage for embeddings and classification to agentic frameworks. Familiarity on evals and measurement frameworks.
Knowledge of advanced statistical methodology and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage, etc).
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.

Nice To Haves

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

Responsibilities

Drive the design, development, and implementation of innovative AI and machine learning solutions that address complex, enterprise scale challenges.
Bridge advanced research and robust engineering, owning the end‑to‑end lifecycle of high‑impact models.
Work collaboratively across the organization with business sponsors, development teams, and engineering partners.
Identify and translate advanced analytical techniques, applications, and strategies into practical production ready solutions.
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.
Create value adding solutions that solve real business problems.
Support multiple business units across Schwab from enterprise services such as Marketing to client and product groups like Investor and Advisor Services.