Quantitative Financial Analyst I

Clearwater Analytics (CWAN); Boise (ID); On-site; USD 90,000 - 130,000; Full time

Job summary

Clearwater Analytics (CWAN) is seeking an early-career Quantitative Developer to build, test, and maintain financial models, calculation libraries, and data pipelines. The role emphasizes Python development, SQL data extraction, and collaboration with software engineers.

A master’s degree in a quantitative field is expected, with no prior professional experience required. You will replicate models in Python and Excel, participate in testing frameworks, and grow into domain ownership while

Qualifications

• Master's degree in a quantitative field or to be completed before start date.
• Demonstrated programming ability in Python with coursework, thesis, internships, or projects.
• Strong foundation in probability, statistics, linear algebra, and numerical methods.
• Foundational understanding of financial markets, instruments, and investment strategies.
• Excellent written and verbal communication, ability to explain quantitative work to non-technical audiences.

Responsibilities

• Assist senior Quantitative Developers and Analysts in researching and implementing new calculations.
• Write clear, tested Python code following team standards and contribute to shared libraries.
• Replicate mathematical models in Excel and Python for client analytics tie-outs.
• Perform acceptance, regression, and integration testing of financial models.
• Write and manage SQL queries to extract data for model inputs and validation.
• Develop data pipeline components to source, normalize, and validate data.
• Build automations to simplify analytical and documentation tasks.
• Maintain internal documentation and communicate findings to stakeholders.

Skills

Python programming

Numerical methods

Statistics

Linear algebra

Financial markets knowledge

Communication

Education

Master's degree in Financial Engineering/Finance/Engineering/Math/CS

Tools

SQL

Git

Excel

Job description

Job Summary: The Quantitative Developer builds, tests, and maintains the financial models, calculation libraries, and data pipelines that power Clearwater’s analytics. This is an early-career opening intended for candidates completing a master’s program in a quantitative field. Quantitative Developers learn Clearwater’s financial models and data model, implement calculations as tested and reviewed code alongside software engineering teams, and grow into ownership of a domain over time. The role blends applied quantitative finance with hands-on software development, and no prior professional experience is required — we expect strong programming fundamentals and a solid quantitative foundation, and will teach the rest. Responsibilities:Assist senior Quantitative Developers and Quantitative Financial Analysts in researching and implementing new calculations as part of larger projects.Write clear, tested Python that follows team standards, and contribute to the shared libraries and internal tooling used across the team through the normal code review process.Accurately replicate existing mathematical models in Excel and Python, including client analytics tie-outs.Perform acceptance, regression, and integration testing of financial models using the existing automated testing frameworks.Write, read, and edit SQL queries to extract security, position, and market data for model inputs, validation, and ad-hoc analysis.Implement numerical and statistical methods — Monte Carlo simulation, solvers and root-finding, interpolation — under the direction of more senior team members.Build and maintain components of the data pipelines that source, normalize, and validate data consumed by financial models.Research and learn the data model for your domain, including the data consumed and produced by the code base.Assist operations teams in understanding how data inputs impact calculations, and assist developers in analyzing unexpected regressions for a code change.Identify and build small automations, including the effective use of AI-assisted development tools, to simplify recurring analytical, validation, and documentation work.Proactively update internal documentation to reflect new features and calculation methodology.Answer questions within your domain about calculation methodology for internal stakeholders, and communicate findings clearly to non-technical audiences.Build domain knowledge continuously, and stay current with quantitative analysis techniques and software engineering practice.Requirements:Master’s degree, completed or to be completed before the start date, in Financial Engineering, Finance, Economics, Engineering, Mathematics, Statistics, Physics, Computer Science, or a similar quantitative fieldNo prior professional experience requiredDemonstrated programming ability in Python — evidenced through coursework, thesis work, internships, or personal projects — including writing reusable functions and modules, working with structured data, and implementing financial or mathematical calculationsStrong quantitative foundation including probability, statistics, linear algebra, and numerical methodsFoundational understanding of financial markets, instruments, and investment strategiesStrong written and verbal communication skills, including the ability to explain quantitative work to non-technical audiencesReceptive to direction and feedback, and willing to escalate roadblocks earlyDesired Experience or Skills:Exposure to SQL and relational databasesFamiliarity with version control (Git) and collaborative software development workflowsInternship, co-op, or research experience in financial services, fintech, or quantitative researchCoursework or research in Fixed Income Securities and Risk Analytics, including cash flow analysis, OAS, duration and convexityCoursework or research in Stochastic Modeling of Financial MarketsInterest rate modeling (e.g., Hull-White, HJM, LIBOR Market Model) and model calibrationExposure to Derivatives Pricing Models and computing Implied VolatilityProficiency with scientific Python libraries (NumPy, pandas, SciPy)Experience building data pipelines that source and normalize data from multiple systems or vendorsAdvanced Excel modellingEffective use of AI coding assistants and LLM-based tooling within a development workflowFamiliarity with automated testing frameworks and the software development process, i.e. AgileProgress toward or completion of the CFA, FRM, or CQF