Quantitative Software Engineer - Research Platform

Charles Schwab; San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

401(k) with company match

Sabbatical after 5 years

Parental leave and family building

Tuition reimbursement

Health, dental, and vision insurance

Job summary

Charles Schwab is seeking a Quantitative Software Engineer - Research Platform to help shape Schwab’s research technology ecosystem. You will build scalable data, analytics, and platform capabilities that accelerate quantitative research and product innovation.

You will work closely with researchers, engineers, product owners, and business partners to solve complex data challenges, enable data-driven decision-making, and create reusable solutions that improve efficiency and speed to market

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering, or related discipline or equivalent practical experience.
• 6+ years of software engineering in data-intensive apps, analytics platforms, or quantitative systems using Python and/or similar languages.
• Experience partnering with researchers/analysts/product owners to deliver data-driven tech solutions.
• Experience building scalable data pipelines and data platforms for structured/unstructured data.
• Proficiency in data modeling for storage, integration, retrieval, and analysis.
• Experience implementing data quality controls, governance, lineage, and observability.
• Experience building software capabilities supporting quantitative research and data-intensive workloads.
• Experience with CI/CD, source control, automated testing, containerization, deployment automation.
• Experience creating data visualizations and dashboards for actionable insights.
• Experience collaborating in Agile and DevOps environments.

Responsibilities

• Shaping Schwab’s research tech ecosystem by building scalable data and analytics capabilities.
• Collaborating with researchers, engineers, product owners, and business partners to deliver data-driven solutions.
• Developing and maintaining data pipelines and data platforms for diverse datasets.
• Delivering dashboards and visualization tools that enable actionable client insights.
• Contributing to platform direction, architecture, and governance for investment research workflows.

Skills

Python

Data pipelines

CI/CD

Testing frameworks

Data visualization

Agile/DevOps

Cloud platforms

Education

Bachelor's degree in CS/IS/Math/Engineering

Advanced degree (preferred)

Tools

Snowflake

Google Cloud Platform (GCP)

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 and financial planning. Within Schwab Asset Management Technology, this role helps power the research, analytics, and investment capabilities that support clients, advisors, and investment professionals.

As a Quantitative Software Engineer - Research Platform, you will help shape Schwab’s research technology ecosystem by building scalable data, analytics, and platform capabilities that accelerate quantitative research and product innovation. Working closely with researchers, engineers, product owners, and business partners, you will solve complex data and technology challenges, enable data-driven decision‑making, and create reusable solutions that improve efficiency, speed to market, and platform adoption across investment disciplines. This role offers the opportunity to influence strategic platform direction while delivering technology that supports investment research and actionable client insights.

What you have

Required Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering, or a related technical discipline, or equivalent practical experience.
• 6+ years of software engineering experience developing data‑intensive applications, analytical platforms, or quantitative systems using Python and/or similar languages such as R, MATLAB, or Julia.
• Experience partnering with researchers, analysts, product owners, or business stakeholders to deliver data‑driven technology solutions.
• Experience designing, developing, and supporting scalable data pipelines and data platforms for structured and unstructured datasets.
• Proficiency designing and implementing data models for efficient storage, integration, retrieval, and analysis.
• Experience implementing data quality controls, monitoring, governance, lineage, and observability practices.
• Experience developing software capabilities that support quantitative research, analytics, or other data‑intensive workloads.
• Experience applying modern software engineering and CI/D CD practices, including source control, automated testing, containerization, and deployment automation.
• Experience building automated testing frameworks for integration, regression, and data validation testing.
• Experience developing data visualizations, dashboards, and analytical tools that enable actionable insights.
• Experience collaborating within Agile and DevOps environments across engineering, product, architecture, and governance teams.

Preferred Qualifications:

• Advanced degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related technical discipline.
• Experience with cloud‑native data platforms and architectures; Snowflake and/or Google Cloud Platform (GCP) experience preferred.
• Experience building distributed data processing, streaming, or large‑scale analytics solutions.
• Experience developing reusable platforms, frameworks, libraries, or shared services.
• Experience supporting quantitative investment research, model development, portfolio analytics, backtesting, or investment management workflows.
• Experience analyzing large, complex datasets to identify meaningful insights and opportunities.
• Experience developing self‑service analytics, visualization, and researcher productivity tools.
• Experience implementing model lifecycle management, monitoring, observability, and risk‑control frameworks.
• Experience applying machine learning, generative AI, or advanced analytics capabilities to business problems.
• Ability to influence technology strategy, architecture decisions, engineering standards, and platform direction.
• Strong verbal and written communication skills with technical and non‑technical audiences.
• Demonstrated commitment to innovation, experimentation, and continuous improvement.

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

What’s in it for you

At Schwab, you’re empowered to shape your future. We champion your growth through meaningful work, continuous learning, and a culture of trust and collaboration—so you can build the skills to make a lasting impact. Our Hybrid Work and Flexibility approach balances our ongoing commitment to workplace flexibility, serving our clients, and our strong belief in the value of being together in person on a regular basis.

We offer a competitive benefits package that takes care of the whole you – both today and in the future:

• 401(k) with company match and Employee stock purchase plan
• Paid time for vacation, volunteering, and 28‑day sabbatical after every 5 years of service for eligible positions
• Paid parental leave and family building benefits
• Tuition reimbursement
• Health, dental, and vision insurance