Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

About the Role

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. This role advances Schwab’s capabilities by driving the design, development, and implementation of innovative AI and machine learning solutions that address complex, enterprise scale challenges.

Responsibilities

Drive the design, development, and implementation of AI and machine learning solutions.
Own the end-to-end lifecycle of high-impact models.
Collaborate 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 data scientists, ML engineers, and product owners throughout a project lifecycle.
Perform data extraction and preparation, feature engineering, and model design and development.
Create value adding solutions that solve real business problems.
Support multiple business units across Schwab.

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.
Strong foundational knowledge of 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.

Skills

Machine Learning algorithm design and implementation (Gradient Boosting Trees, GLM/Regression, Random Forest, Neural Networks, K-Means clustering etc.)
Understanding of algorithm advantages and drawbacks.
Experience with modern large language models (LLMs) for embeddings, classification, and agentic frameworks.
Familiarity with LLM evaluation and measurement frameworks.
Advanced statistical methodology and concepts (regression, properties of distributions, time series analysis and modeling, statistical tests and proper usage).
Business Acumen: Understanding the bigger picture for customers and the business.
Python
Software engineering methodologies
Dataiku
Google Cloud (Vertex AI, Big Query)
MLops and model monitoring
Working in regulated environments

Location

On-site in specified location(s)

Work Type

On-site
Full-time

Experience Level

Demonstrated professional experience in delivering production AI and Data Science products

Education Level

MS/PHD in a quantitative field

Salary/Compensations

Eligible for bonus or incentive opportunities

Benefits

Continuous learning
Meaningful work
Collaboration
Deepen technical expertise
Explore innovative approaches
Ownership of solutions
Knowledge sharing
Professional development
Work alongside experienced AI, engineering, and business leaders
Career growth opportunities

About the Company

Schwab is a 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.
Schwab is committed to expanding access to investing and financial planning.
We believe in the importance of in-office collaboration.