Quantitative Software Engineer - Research Platform
Charles Schwab1 day ago
Base Salary
$175k - $230k/yr
Responsibilities
- Build scalable data, analytics, and platform capabilities for quantitative research and investment product innovation.
- Design and support data pipelines and platforms for structured and unstructured datasets.
- Develop data models, data quality controls, monitoring, governance, lineage, and observability practices.
- Create software capabilities, reusable platforms, frameworks, libraries, and shared services for quantitative research and analytics.
- Implement automated integration, regression, and data validation testing frameworks.
- Develop data visualizations, dashboards, analytical tools, and self-service researcher productivity tools.
- Apply software engineering, source control, testing, containerization, and deployment automation practices.
- Collaborate with researchers, engineers, product owners, business partners, architecture teams, and governance teams.
- Influence technology strategy, architecture decisions, engineering standards, and platform direction.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering, or a related technical discipline, or equivalent practical experience.
- At least 6 years of software engineering experience developing data-intensive applications, analytical platforms, or quantitative systems.
- Experience with Python and/or similar languages such as R, MATLAB, or Julia.
- Experience designing scalable data pipelines, data platforms, data models, and data-intensive software capabilities.
- Experience implementing data quality, monitoring, governance, lineage, observability, automated testing, and deployment practices.
- Experience partnering with researchers, analysts, product owners, or business stakeholders to deliver data-driven solutions.
- Preferred advanced degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related discipline.
- Preferred experience with Snowflake, Google Cloud Platform, distributed data processing, streaming, large-scale analytics, quantitative investment research, portfolio analytics, backtesting, or investment management workflows.
- Preferred experience with machine learning, generative AI, advanced analytics, model lifecycle management, and risk-control frameworks.
- Strong verbal and written communication skills and the ability to influence technology strategy and platform direction.
Benefits
- The role is intended to be performed onsite in the specified location or locations.
- The position is eligible for bonus or incentive opportunities.
Tech Stack
Categories
Data Engineering
About Charles Schwab
Charles Schwab provides brokerage, banking, and wealth management services for individual investors and independent investment advisors. Its business spans trading platforms, advisory and custody services (Schwab Advisor Services), ETFs and mutual funds, and a U.S. bank offering deposits and lending. Founded in 1971 and headquartered in Westlake, Texas, Schwab is publicly traded on the NYSE (SCHW) and expanded its retail and advisor footprint through the acquisition of TD Ameritrade.