Google Data Science Jobs in Austin, TX (NOW HIRING)

AI is reshaping how clients engage with financial services, and Schwab is looking for a proven data science leader to help define what comes next. As Director of Data Science within Schwab’s AI and Data Science organization, part of the broader Data organization, you will lead high-impact work that uses machine learning, and AI to inform business decisions, elevate client experiences, and strengthen Schwab’s competitive edge.

This is a highly visible leadership opportunity within an organization that supports many of Schwab’s most important business areas, from marketing to client service, creating room to influence forward-looking AI opportunities across the enterprise. The role reports directly to the Head of the AI and Data Science organization for Charles Schwab and offers the scope, visibility, and strategic partnership that experienced AI/ML leaders look for in their next career-defining move.

You will lead a cross-functional organization of around 10, with a heavy focus on Marketing, while also helping expand Schwab’s capabilities in NLP/NLU, LLMs, and Generative AI as priorities evolve. This is an opportunity to shape practical, enterprise-scale AI solutions that move beyond experimentation and into measurable business and client impact.

What you’ll do:

• Lead, mentor, and develop managers and individual contributors while fostering a culture of innovation, accountability, and technical excellence.
• Partner with senior business leaders to identify where AI can create the greatest value, then translate priorities into product roadmaps, operating plans, and measurable outcomes.
• Translate business strategy into technical execution by partnering with senior leaders to convert high‑level business objectives into clear, actionable data science and AI roadmaps that address critical business and technology challenges.
• Design and build end‑to‑end machine learning systems by defining scalable, reliable, and maintainable architectures that support data ingestion, feature generation, model training, evaluation, deployment, and monitoring in production environments.
• Set and elevate engineering standards for data science by establishing best practices that treat data science as a rigorous engineering discipline, including modular code design, testing, version control, and production readiness.
• Advance technical capabilities in emerging areas by leading complex initiatives involving advanced machine learning, real‑time and low‑latency inference, or other evolving technologies that require deep technical expertise and comfort with ambiguity.
• Stay ahead of emerging trends in data science, analytics, AI, and responsible innovation, bringing forward ideas that can create measurable value for Schwab and its clients.

Required Qualifications:

• Master’s degree in a quantitative field such as engineering, physics, computer science, statistics, or a related discipline.
• 6+ years of direct leadership experience managing data science teams that develop and deploy production AI products.
• 12+ years of AI/ML experience, including strong knowledge of modern algorithms, statistics, model development, and applied machine learning.
• 4+ years of experience with NLP, NLU, LLMs, or Generative AI in a client-facing enterprise environment.
• Experience leading AI or data science products through the full lifecycle, from strategy and design through testing, rollout, adoption, and continuous improvement.
• Strong executive communication skills with the ability to influence, educate, and align stakeholders at all levels of the organization.
• Ability to translate business and product needs into technology requirements while partnering effectively with engineering and platform teams.
• Experience leading geographically distributed, cross-functional teams in a complex enterprise environment.

Preferred Qualifications:

• Experience in cloud-based solutions such as Google Cloud Platform.
• Financial services experience, particularly in a regulated, client-facing environment.
• Experience with Marketing Mix modeling and multi touch attribution.