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About the Role

Shape Schwab’s research technology ecosystem by building scalable data, analytics, and platform capabilities that accelerate quantitative research and product innovation. 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. Influence strategic platform direction while delivering technology that supports investment research and actionable client insights.

Responsibilities

Building scalable data, analytics, and platform capabilities.
Solving complex data and technology challenges.
Enabling data-driven decision-making.
Creating reusable solutions to improve efficiency, speed to market, and platform adoption.
Influencing strategic platform direction.
Delivering technology that supports investment research and actionable client insights.
Designing, developing, and supporting scalable data pipelines and data platforms.
Implementing data quality controls, monitoring, governance, lineage, and observability practices.
Developing software capabilities that support quantitative research, analytics, or other data-intensive workloads.
Building automated testing frameworks for integration, regression, and data validation testing.
Developing data visualizations, dashboards, and analytical tools.
Collaborating within Agile and DevOps environments.
Developing reusable platforms, frameworks, libraries, or shared services.
Supporting quantitative investment research, model development, portfolio analytics, backtesting, or investment management workflows.
Analyzing large, complex datasets to identify meaningful insights and opportunities.
Developing self-service analytics, visualization, and researcher productivity tools.
Implementing model lifecycle management, monitoring, observability, and risk-control frameworks.
Applying machine learning, generative AI, or advanced analytics capabilities to business problems.
Influencing 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.
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.
Proficiency designing and implementing data models for efficient storage, integration, retrieval, and analysis.
Experience applying modern software engineering and CI/CD practices, including source control, automated testing, containerization, and deployment automation.
Experience collaborating within Agile and DevOps environments across engineering, product, architecture, and governance teams.
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 supporting quantitative investment research, model development, portfolio analytics, backtesting, or investment management workflows.
Experience implementing model lifecycle management, monitoring, observability, and risk-control frameworks.
Strong verbal and written communication skills with technical and non-technical audiences.
Demonstrated commitment to innovation, experimentation, and continuous improvement.

Skills

Python
R
MATLAB
Julia
Data Pipelines
Data Platforms
Data Models
Data Quality Controls
CI/CD practices
Source Control
Automated Testing
Containerization
Deployment Automation
Automated Testing Frameworks
Data Visualizations
Dashboards
Analytical Tools
Agile
DevOps
Snowflake
Google Cloud Platform (GCP)
Distributed Data Processing
Streaming
Large-scale Analytics
Machine Learning
Generative AI
Advanced Analytics

Location

On-site

Work Type

On-site
Full-time

Experience Level

6+ years of software engineering experience

Education Level

Bachelor’s degree in Computer Science, Information Systems, Mathematics, Engineering, or a related technical discipline, or equivalent practical experience.
Advanced degree in Computer Science, Engineering, Mathematics, Quantitative Finance, or a related technical discipline.

Salary/Compensations

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

About the Company

At Schwab, you’re empowered to make an impact on your career.
Innovative thought meets creative problem solving, helping us challenge the status quo and transform the finance industry together.
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.