Job Description

Your Opportunity

At Schwab, you’re empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together. We believe in the importance of in-office collaboration and fully intend for the selected candidate for this role to work on site in the specified location(s).

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.

What you have

Required Qualifications

• 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

Preferred Qualifications

• 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

In addition to the salary range, this role is eligible for bonus or incentive opportunities.