The Structured Products market makes up nearly $10 trillion of US public and private bond market debt. Banks use financial engineering to transform a variety of assets, such as residential and commercial mortgages, auto and student loans, and credit card debt, into securities that are structured to meet nearly any investor appetite.

We are responsible for developing and maintaining a large library of cashflow models and data for these securities. You will be developing cutting-edge modeling tools to improve the accuracy and coverage of our product. You will be creating cashflow models for esoteric asset sectors and working closely with our apps/infrastructure team to handle analytics for new asset sectors. Our team builds end-to-end solutions for all projects. We are working on multiple projects that would increase our deal coverage in asset sectors such as Student Loan securitizations and Collateralized Loan Obligations while building infrastructure necessary to help us meet our goal of modeling all varieties of structured products. As part of our team, your input on technology will be crucial to the development and growth of our product.

We’ll trust you to:

• Reverse engineer and manage a large library of financial models relevant to portfolio managers and traders
• Collaborate with our developers to design and implement internal system tools, including test validations, automated product reports, and workflows
• Partner with product managers in understanding clients' workflows to design and build software solutions that meet and exceed their expectations
• Proactively lead initiatives by driving definition of requirements, project estimations, sprint scheduling, risk mitigation and tactical deployment

You’ll need to have:

• BA, BS, MS, PhD in Computer Science, Engineering or related technology field
• 1+ years of experience programming
• Familiarity with data structures, algorithms and object-oriented design
• Strong communication, analytical and problem-solving skills
• Ability to take on detailed assignments in a fast paced environment
• A Bachelor's degree in Computer Science, Math, Engineering, Finance or equivalent experience