This role sits at the intersection of software engineering, data engineering, and applied statistics, translating complex mathematical and statistical models into scalable, maintainable systems used in real‑world financial decision‑making. You will work closely with a globally distributed quantitative risk team, contributing solutions that are reliable, performant, and production‑ready.
Your Primary Responsibilities
Implement and productionize quantitative, statistical, and mathematical models using Python
Engineer and maintain scalable solutions that run reliably in production environments
Support quantitative risk model implementations to support the Financial Risk Management department
Design, build, and maintain data pipelines leveraging Python, Snowflake, and relational databases
Translate existing analytical, statistical, or theoretical models into clean, maintainable Python code
Own solutions end‑to‑end, from model implementation through deployment, monitoring, and production support
Collaborate closely with quantitative analysts, risk partners, and global stakeholders
Provide L3 production support on an as‑needed basis via PagerDuty (issue‑based coverage; no fixed on‑call rotation)
Contribute within an Agile development environment, following strong engineering and control practices
Ensure solutions meet standards for performance, reliability, documentation, and operational controls
Qualifications
Bachelor’s degree preferred or equivalent practical experience
Minimum of 6 years of related experience
Talent Needed for Success
Strong experience in Python software development for analytical model implementation, building production‑grade code (beyond scripting or notebooks)
Hands‑on experience working with quantitative, statistical, or mathematical models
Experience with Snowflake or similar cloud‑based data platforms
Solid foundation in statistics, data analysis, or quantitative concepts
Background in financial services, risk management, capital markets, or related domains
Experience working within an Agile delivery model
Strong communication skills and ability to collaborate across global teams
Experience supporting production systems, including L3 support when required
Nice to Have Skills
Experience implementing or productionizing risk, capital, or liquidity models
Exposure to AI / machine learning concepts (baseline understanding; this is not a data scientist or research role)
Prior experience supporting quantitative risk management teams
Experience converting academic or theoretical models into reliable production software
The salary range is indicative for roles at the same level within DTCC across all US locations. Actual salary is determined based on the role, location, individual experience, skills, and other considerations. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.
