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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Scientist - **Company:** Charles Schwab Inc. - **Location:** Austin, TX, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software Quality, Computer Engineering, Continuous Integration, Python (Programming Language), Machine Learning, Natural Language Processing, Recommender Systems, Software Deployment, SQL Databases, Unstructured Data, Cloud Platform System, Data Ingestion, Retrieval-Augmented Generation, Large Language Models, Deep Learning, Build Management, Machine Learning Operations, Software Version Control, Data Pipelines - **Published:** July 23, 2026 - **Apply:** https://dejobs.org/x/x/72594035750647E7816C096929AA32E8/job/ ## About the Role * 10+ years of experience in data science and machine learning, including 3+ years operating as a senior- or staff-level individual contributor with significant technical ownership. * Advanced degree (Master's or PhD) in a quantitative field such as computer engineering, statistics, mathematics, physics, chemistry, or a related discipline. * 8+ years of hands - on experience using Python and SQL to develop production-grade, modular, and optimized code. * Demonstrated ability to architect and deliver end-to-end machine learning solutions, with evidence of at least two production systems supporting real-time or low-latency use cases. * Proven experience developing supervised and unsupervised machine learning solutions, with delivery of five or more distinct models or analytical systems supported by documented evaluation metrics and performance tracking. * Experience applying natural language processing techniques to unstructured data, supported by two or more delivered analyses or production components. * Practical experience designing large language model solutions (such as retrieval-augmented generation, agent workflows, or fine-tuning), including at least one end-to-end LLM system deployed for production or broad internal use. * Strong software engineering fundamentals, including version control, CI/CD, and MLOps practices, demonstrated through three or more production deployments. * Proven ability to convert business requirements into technical roadmaps, including ownership or co-ownership of two or more roadmaps reviewed with senior stakeholders and delivered against defined milestones. Preferred Qualifications * Experience working in financial services or other highly regulated industries. * Strong background in statistics, forecasting, or causal inference. * Hands-on experience architecting machine learning solutions within cloud ecosystems. * Experience building, maintaining, and optimizing data pipelines that support machine learning workflows. * Experience developing large-scale recommender or personalization systems. * A demonstrated commitment to mentorship, including coaching senior data scientists or engineers and elevating team capability through feedback and code quality. ## Description * 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. * 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. * 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, recommender systems, real-time and low-latency inference, or other evolving technologies that require deep technical expertise and comfort with ambiguity. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Pioneering AI Assistants in Banking](https://www.wearedevelopers.com/videos/1627-pioneering-ai-assistants-in-banking) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Analyst Salary in Switzerland](https://www.wearedevelopers.com/magazine/276-data-analyst-salary-in-switzerland) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary Austria](https://www.wearedevelopers.com/magazine/275-data-analyst-salary-austria) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)