Director of Risk Management Software Engineering

***We are unable to sponsor for this permanent full-time role***

***Position is bonus eligible***

Prestigious Financial Institution is currently seeking a Director of Risk Management Software Engineering. Candidate will be responsible for functions within Quantitative Risk Management for developing and maintaining risk models for margin, clearing fund and stress testing with the focus on developing and maintaining risk model software in production, and environments and infrastructure used in model implementation and testing.

Responsibilities:

• Collaborate with other developers, quantitative analysts, business users, data & technology staff to expand QRM’s technical capabilities for model development, back-testing and monitoring.
• Develop and maintain software and environments used to implement and test systems for pricing, margin risk and stress testing of financial products and derivatives.
• Configure and manage resources in the local and AWS cloud environments and deploy QRM’s software on these resources.
• Develop CI/CD pipelines.
• Configure, execute, and monitor execution pipelines for model testing, back-testing and monitoring.
• Contribute to development of QRM’s databases and ETLs.
• Integrate model prototypes, model library and model testing tools using best industry practices and innovations.
• Create unit and integration tests; build and enhance test automation tools.
• Participate in code reviews and demo accomplishments.
• Write technical documentation and user manuals.
• Provide production support and perform troubleshooting.

• Provide hands-on technical leadership and active coordination of tasks and priorities.
• Provide guidance and support for the team and reporting for the management.

Qualifications:

• Strong programing skills. Able to read and/or write code using a programming language (e.g., Java, C++, Python, etc.) in a collaborative software development setting: The role requires advanced coding, database and environment manipulation skills.
• Track record of complex production implementations and a demonstrated ability in developing and maintaining enterprise level software, including in the cloud environment.
• Proficiency in technical and/or scientific documentation (e.g., white papers, user guides, etc.)
• Strong problem-solving skills: Be able to accurately identify a problem's source, severity, and impact to determine possible solutions and needed resources.
• Experience with Agile/SCRUM or another rapid development framework.
• Financial products knowledge is a plus: understanding of markets and financial derivatives in equities, interest rate, and commodity products.
• Background in Financial mathematics is a plus: derivatives pricing models, stochastic calculus, statistics and probability theory, linear algebra.
• Master’s degree or equivalent in a computational or numerical field such as computer science, information systems, mathematics, physics
• 10+ years of experience as a software developer with exposure to the cloud or high-performance computing areas

Technical Skills:

• Proficiency in Java (preferred) or another object-oriented language is required, including effective application of design patterns and best coding practices.
• DevOps experience, with a good command of CI/CD process and tools (e.g., Git, GitHub, Gradle, Jenkins, Docker, Helm, Harness). Experience in containerized deployment in cloud environments.
• Experienced with cloud technology (AWS preferred), infrastructure-as-code (e.g. Terraform), managing and orchestrating containerized workloads (e.g. Kubernetes).
• Experience with logging, profiling, monitoring, telemetry (e.g. Splunk, OpenTelemetry).
• Good command of database technology and query languages (SQL) and non-relational DB and other Big Data technology, including efficient storage and serialization protocols (e.g. Parquet, Avro, Protocol Buffers).
• Experience with automated quality assurance frameworks (e.g., Junit, TestNG, PyTest, etc.).
• Experience with high performance and distributed computing.
• Experience with productivity tools such as Jira, Confluence, MS Office.
• Experience with scripting languages such as Python is a plus.
• Experience with numerical libraries and/or scientific computing is a plus.