Quantitative Software Engineer - Research Data and Models (PL)

Charles Schwab Inc.•San Francisco, CA

3d•$195,000 - $250,000•Onsite

About The Position

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.

Requirements

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

Nice To Haves

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
Demonstrated ability to drive alignment across multiple stakeholders with competing priorities

Responsibilities

Lead a team responsible for building and modernizing research platforms, scalable data solutions, and quantitative models.
Enable investment research across multiple asset classes.
Combine technical leadership, problem-solving, and partnership with researchers, product leaders, and engineers.
Deliver reliable, high-quality capabilities that translate research into business value.
Balance innovation, operational excellence, and strategic decision-making.
Foster a collaborative, agile culture focused on continuous improvement, transparency, and impactful outcomes.