Director, Quantitative Software Engineer

Charles Schwab Inc.•San Francisco, CA

3d•$230,000 - $300,000•Onsite

About The Position

Schwab Technology Services enables the future of how clients manage their money by delivering innovative and reliable technology solutions that support investing, financial planning, and wealth management. Within Schwab Asset Management Technology, you will help advance the platforms, data, and research capabilities that power investment insights and product innovation. As a Director, Quantitative Software Engineer - Research Lead, you will partner closely with quantitative researchers, investment professionals, and technology teams to accelerate research, model development, and product delivery. You will solve complex technical challenges, design scalable research and data platforms, and transform innovative investment concepts into production-ready solutions. Success in this role requires strong collaboration, analytical thinking, adaptability, and technical leadership as you help build reusable capabilities that improve research effectiveness, support data-driven decisions, and enable the delivery of differentiated investment products across the enterprise.

Requirements

Bachelor's degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related technical field, or equivalent practical experience
8+ years of software engineering experience developing quantitative applications, research platforms, or data-intensive solutions using Python and/or similar languages such as R, Julia, or MATLAB
Experience partnering directly with quantitative researchers, portfolio managers, or investment professionals
Experience designing, building, and supporting scalable data pipelines and analytical platforms
Knowledge of quantitative research workflows, including data acquisition, model development, backtesting, validation, and deployment
Experience designing data models, data integration solutions, and data storage architectures
Experience developing data visualization and analytical tools that support research and decision-making
Experience implementing data governance, lineage tracking, monitoring, and data quality controls
Experience balancing research flexibility with enterprise standards for reliability, reproducibility, security, and supportability
Experience with modern software engineering practices, source control, automated testing, containerization, CI/CD, and deployment automation
Demonstrated ability to lead complex technical initiatives and thrive in ambiguous environments
Strong verbal and written communication skills

Nice To Haves

Advanced degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related field
Experience productionizing quantitative models and research methodologies supporting investment products
Experience building reusable platforms, frameworks, libraries, or shared services
Experience applying AI/ML, generative AI, distributed computing, or cloud-native technologies to research and analytics challenges
Experience influencing technology strategy through investment industry and market insights
Experience developing visualization, exploratory analytics, or decision-support solutions
Demonstrated track record of innovation and continuous improvement
Experience mentoring engineers, researchers, or other technical professionals
Ability to communicate complex quantitative and technical concepts to diverse audiences
Demonstrated integrity, sound judgment, and discretion when handling sensitive information

Responsibilities

Partner closely with quantitative researchers, investment professionals, and technology teams to accelerate research, model development, and product delivery.
Solve complex technical challenges.
Design scalable research and data platforms.
Transform innovative investment concepts into production-ready solutions.
Build reusable capabilities that improve research effectiveness, support data-driven decisions, and enable the delivery of differentiated investment products across the enterprise.