DTCC

Senior Quantitative Software Engineer

DTCC$120K — $150K *
Finance & Insurance
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree preferred or equivalent practical experience
  • Minimum of 6 years of related experience
  • Strong experience in Python software development for analytical model implementation
  • Hands-on experience 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, or capital markets

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 for the Financial Risk Management department
  • Design, build, and maintain data pipelines leveraging Python and relational databases
  • Translate analytical, statistical, or theoretical models into clean, maintainable Python code
  • Own solutions end-to-end, including deployment and production support
  • Collaborate closely with quantitative analysts and global stakeholders
  • Provide L3 production support as needed via PagerDuty
  • Contribute within an Agile development environment

Benefits

  • Collaborative environment with global stakeholders
  • Opportunity to work on production-grade systems
  • Exposure to both quantitative and software engineering disciplines
  • Flexible support on production systems with issue-based coverage
  • Strong focus on performance, reliability, and operational controls
Full Job Description
Job Description

The Impact You Will Have in This Role

As a Quantitative Software Engineer, you will play a key role in designing and delivering production-grade Python solutions that support critical quantitative risk initiatives, that strengthen the Financial Risk Management posture of DTCC.

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.

About DTCC

The Depository Trust & Clearing Corporation (DTCC) is a financial services company that provides clearing, settlement, and information services for the global financial industry. DTCC was founded in 1999 and is headquartered in New York City. The company operates through subsidiaries that provide services such as trade matching, risk management, and asset servicing. DTCC is owned by its users, which include broker-dealers, banks, and other financial institutions. The company is committed to reducing risk and increasing efficiency in the financial markets.
Learn more about DTCC
Size
4,000 employees
Industry
Founded
1973

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