Schwab's Wealth and Asset Management (WAM) Engineering organization is looking to evolve its key data platforms and deliver models, analytics, and reporting projects to drive cutting-edge research and product development activities, ultimately helping clients reach their financial goals.
Requirements
- 4+ years of experience with Python or Java
- Proficiency in one or more programming languages used for quantitative investment model development and analysis (e.g., Python or R)
- Experience building data pipelines and related processes with large financial research timeseries datasets
- Proficiency in designing quant-research optimized data models that support efficient data retrieval and aggregation of financial datasets, including complex hierarchical structures
- Familiarity in developing distributed data processing and streaming frameworks and architectures
- Experience leveraging continuous integration/development tools (e.g. Jenkins, Docker, Containers, OpenShift, Kubernetes, and container automation) in a CI/CD pipeline
- Utilizes statistical techniques and hypothesis testing to analyze large datasets to support decision-making
Responsibilities
- Design, implement and maintain software solutions that enable quantitative research
- Apply knowledge and take a lead role in implementing quantitative investment research products within the designated business area to support organizational goals and objectives, including gathering and collecting time series financial data, and developing quantitative models, analytics, and tests
- Apply knowledge and take a lead role in implementing quantitative systems architecture within the designated business area to support organizational goals and objectives, including designing and maintaining financial research data systems that leverage distributed/cloud computing, data analytics, and machine learning
- Develop control frameworks required to deploy and manage quant models in production environments
- Lead data engineering implementation efforts for data processing pipelines that curate financial datasets into representations fit for model research and production applications
- Co-develop production code in conjunction with quant researchers to deliver performant software (supported by comprehensive test coverage) that meet investment objectives while minimizing the risk of model errors; manage SDLC processes to enable CI/CD
- Design, develop, test, and deploy systematic analytics pipelines using machine learning / statistical analysis frameworks
Other
- 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).
- The ideal candidate is expected to be a self-starter who can take responsibility for building significant capabilities within the broader research platform.
- This role works within a mature Agile and DevOps model in partnership with our business stakeholders, requiring active engagement with Product Owners, Researchers, Architects, and other Partners — in managing requirements, design, coding, testing (unit and functional), deployment, and post-release support.
- Be a champion of new ways of collaborating with technology and business partners
- Influence and implement improvements and efficiencies in both the technical and non-technical aspects of the development process
