Careers at Charles Schwab

Your opportunity

​​At Charles Schwab, our purpose is simple: we champion client’s goals with passion and integrity. Guided by honesty, mutual respect and a commitment to doing what’s right, we bring innovation, education, and service together to help shape financial futures. Our people are the foundation of our success – they approach their work with curiosity and collaboration, coming together to create solutions that make a meaningful impact for clients and communities. As we expand into India, we are bringing this same culture of inclusion, learning, and opportunity to new talent. Joining us means becoming part of a global team where your work matters and your future can take shape.​

What you have

Key Responsbilities

As a Quantitative Analyst - Investment Research in the SAM Investment Research Technology group, you will play a critical role in delivering cutting-edge research and product development capabilities designed to advance SAM business opportunities and to support the Schwab Center for Financial Research (SCFR) in its mission to provide clients and advisors actionable investment advice. We curate structured and unstructured datasets for both exploratory and product-focused research, and we implement and maintain investment models across multiple asset classes and product categoriess, including equity and fund ratings, thematic investing baskets, multi-asset solutions, factor strategies, and more.

This role will interact with researchers and other business users to help bring together data, analytics, modeling, and operational capabilities into a common ecosystem for all research teams. You will help establish the foundational capabilities, frameworks, and workflows that enable innovative research products, accelerate time-to-market, and promote greater reuse of data and technology assets across the organization. This is an opportunity to help define the future state of quantitative research technology at Schwab.

Required Qualifications

▪ Degree in computer science, information systems, mathematics, engineering, or a related technical discipline, or equivalent practical experience
▪ Five or more years of business systems analysis and/or software engineering experience working with data-intensive applications, quantitative systems, or analytical platforms built with Python and/or similar languages (e.g. R, Matlab, Julia)
▪ Knowledge of financial markets, the investment management business, and associated research practices
▪ Experience partnering with researchers, analysts, product owners, or business stakeholders to gather requirements and implement technology solutions that support data-driven decision-making
▪ Strong background working with large, complex datasets and applying data science methodologies to extract meaning and value for business partners
* Expertise to create data visualizations that drive effective decision-making
▪ Familiarity with data models that enable efficient storage, integration, retrieval, and analysis of complex datasets
▪ Experience designing data quality frameworks and controls, including monitoring, validation, lineage tracking, governance processes, and observability
▪ Proven ability to collaborate effectively within Agile and DevOps environments, partnering with Product Owners, Architects, engineers, and governance teams to deliver high-quality solutions that meet enterprise standards for quality, reliability, and supportability

Preffered Qualifications

▪ Advanced degree in computer science, engineering, mathematics, quantitative finance, or a related technical discipline
▪ Experience supporting quantitative investment research, model development, backtesting, portfolio analytics, performance attribution, or other investment management workflows
▪ Demonstrated ability to uncover complex patterns and insights through advanced analysis of large and diverse datasets
▪ Experience developing data visualization, self-service analytics, and researcher-facing tooling that transforms data into actionable insights and improves decision-making
▪ Experience evaluating and applying emerging technologies, including artificial intelligence, machine learning, generative AI, or advanced analytics techniques, to improve platform capabilities and researcher productivity
▪ Strong verbal and written communication skills, including experience presenting technical concepts, architectural proposals, and analytical findings to both technical and non-technical stakeholders
▪ Track record of championing innovation, experimentation, and continuous improvement through the adoption of new technologies, engineering practices, or operating models