Senior Manager, Data Science

Charles Schwab Inc.•Southlake, TX

1d•$120,000 - $175,000•Onsite

About The Position

The Behavioral AI/ML Analytics (BAMA) team is looking for a dynamic, self-motivated Senior Manager, Data Science. BAMA leverages predictive modeling, advanced analytics, machine learning, and emerging AI technologies to deliver innovative solutions that enhance Schwab's ability to fight financial crime. Supporting Fraud Prevention and Anti-Money Laundering (AML) programs within Financial Risk Management (FRM), the team develops predictive models, AI-powered capabilities, and advanced analytical solutions that solve complex business problems and deliver measurable value. With a broad range of business challenges to address, BAMA provides numerous opportunities to drive meaningful impact through both traditional machine learning and next-generation AI technologies. This is an individual contributor position.

Requirements

Demonstrated ability to independently and collaboratively deliver end-to-end data science solutions that drive business value.
Experience applying data science and machine learning within fraud, AML, payments, financial services, or related domains.
Strong communication skills, with the ability to translate complex analytical and AI concepts into clear business insights.
Curiosity and enthusiasm for learning and adopting new tools, technologies, and techniques.
5+ years of experience in analytics, data science, machine learning, or a related field.
Advanced proficiency in SQL and Python.
Master's degree in a quantitative field or equivalent experience.
Experience with Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, or AI agent frameworks.
Understanding of Responsible AI, model governance, explainability, and AI risk management principles.
Experience with modern AI platforms and tools such as Vertex AI, Gemini, OpenAI, LangChain, or related technologies.

Nice To Haves

Demonstrated experience developing and deploying enterprise GenAI applications within financial services, fraud, AML, risk management, or compliance domains.
Experience with LLM evaluation, AI observability, prompt optimization, RAG architectures, knowledge retrieval systems, and agent-based workflows.
Knowledge of cloud-native AI platforms, particularly Google Cloud Platform (GCP), Vertex AI, Gemini, and related AI services.
Experience leading cross-functional AI initiatives from ideation through production deployment and adoption.
Familiarity with AI governance frameworks, model risk management, and emerging regulatory expectations for GenAI in highly regulated industries.
Experience building scalable AI solutions that integrate predictive modeling, machine learning, and Generative AI capabilities into operational workflows.

Responsibilities

Lead the exploration, development and deployment of predictive modeling, machine learning, and GenAI-powered solutions to enhance fraud detection, AML investigations, risk analytics, and operational efficiency.
Partner with business, technology, and governance teams to identify and prioritize high-value use cases for Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), intelligent automation, and agentic AI systems.
Design, develop, and evaluate AI-assisted investigator tools, knowledge retrieval solutions, and decision-support capabilities while ensuring appropriate model governance, risk controls, and regulatory compliance.
Drive innovation by leveraging cloud-based AI platforms and emerging technologies to improve analyst productivity, decision quality, and customer outcomes.
Communicate analytical findings and AI-driven insights to technical and non-technical stakeholders, influencing strategic decisions and business outcomes.