Quantitative Software Engineer - Research Data and Models (PL)

Charles Schwab Corporation; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Charles Schwab Corporation in San Francisco is seeking a Quantitative Software Engineer - Research Data & Models to lead a team building and modernizing research platforms, data solutions, and quantitative models that enable investment research across asset classes.

The role combines technical leadership with collaboration among researchers, product leaders, and engineers to deliver reliable capabilities, balance innovation with operational excellence, and drive outcomes for clients and business

Qualifications

• Bachelor’s degree or equivalent in a technical field and 6+ years of software engineering.
• Experience with Python or similar (R/Matlab/Julia) in quantitative/analytical contexts.
• Proven ability to partner with researchers to support workflows, data analysis, modeling and backtesting.
• Design, develop, and operate scalable data pipelines for large financial datasets.
• Strong data modeling, integration, and governance practices.
• Experience with CI/CD tools and containerized environments (Jenkins, Docker, OpenShift, Kubernetes).
• Experience building testing frameworks, and leading engineering teams.

Responsibilities

• Lead a team building and modernizing research platforms and data solutions.
• Develop quantitative models to enable investment research across asset classes.
• Collaborate with researchers, product leaders, and engineers to deliver reliable capabilities.
• Balance innovation with operational excellence and drive business value.

Skills

Python

Data pipelines

Data modeling

CI/CD

Leadership

Collaboration

Testing frameworks

Kubernetes

OpenShift

Docker

R/Matlab/Julia

Education

Bachelor’s degree in Computer Science/Engineering/Mathematics

Advanced degree (preferred)

Tools

Jenkins

Docker

OpenShift

Kubernetes

Snowflake

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 Asset Management Technology supports the platforms, data, and research capabilities that help drive investment insights and product innovation across the firm. As a Quantitative Software Engineer - Research Data & Models, you will lead a team responsible for building and modernizing research platforms, scalable data solutions, and quantitative models that enable investment research across multiple asset classes. This role combines technical leadership, problem-solving, and partnership with researchers, product leaders, and engineers to deliver reliable, high-quality capabilities that translate research into business value. Success in this role requires balancing innovation, operational excellence, and strategic decision-making while fostering a collaborative, agile culture focused on continuous improvement, transparency, and impactful outcomes for clients and business partners.

What you have

Required Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering, or a related technical field, or equivalent experience
• 6+ years of software engineering experience supporting quantitative or analytical systems using Python or similar languages such as R, Matlab, or Julia
• Experience partnering with quantitative researchers to support research workflows, data analysis, modeling, and backtesting
• Experience designing, developing, and operating scalable data pipelines for large and complex financial datasets
• Strong knowledge of data modeling, data integration, and data management principles
• Experience implementing data quality controls, monitoring, validation, lineage tracking, and governance practices
• Experience with CI/CD tools and technologies such as Jenkins, Docker, OpenShift, Kubernetes, and containerized environments
• Experience building testing frameworks, including integration and regression testing
• Experience leading engineering teams, coaching talent, and supporting career development
• Proven ability to collaborate with business and technology stakeholders to prioritize work and deliver measurable business outcomes
• Experience managing complex technology initiatives within regulated environments

Preferred Qualifications:

• Advanced degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related discipline
• Experience with modern data lake architectures and platforms, including Snowflake
• Experience designing distributed computing solutions for large-scale data processing and analytics
• Experience leading cloud adoption, platform modernization, or enterprise technology transformation efforts
• Strong understanding of investment research methodologies, factor modeling, portfolio construction, risk analytics, performance attribution, or backtesting
• Experience influencing business and technology strategy through data-driven decision-making
• Excellent communication skills with the ability to present complex technical concepts to diverse audiences
• Experience mentoring technical talent and building organizational capability across teams