# PeerIQ: Credit Quant

Developing statistical and quantitative models to support prepayment, default and loss forecasting; Basel and CCAR; pricing and valuation; and other economic calculations.

**Company: PeerIQ**

**Location: New York City, NY**

**Web: www.peeriq.com**

**DESCRIPTION**

PeerIQ is a New York-based financial information services company that is creating tools to analyze, access, and manage risk in the peer-to-peer lending sector.

We are looking for an exceptional credit quant with experience in the loan space. The candidate will be responsible for developing statistical and quantitative models to support prepayment, default and loss forecasting; Basel and CCAR; pricing and valuation; and other economic calculations. The ideal candidate will be able to lead in the full lifecycle of quantitative development ranging from model development, prototyping, validation, implementation and ongoing maintenance.

The ideal candidate must be a self-starter, able to dive right in and start working with large datasets. You have a deep interest in innovation in financial markets and thrive in a high-velocity, unstructured start-up environment.

**RESPONSIBILITIES**

- Design, maintain, and update algorithms, models, and related tools for the automatic and statistical validation of consumer loan data, including the calculation and refinement of credit risk curves
- Research and implementation of models for new consumer credit instruments and related financial products
- Document and communicate modeling approach, process, and related findings to internal and external clients as necessary
- Maintain large data sets using advanced statistical/modeling tools and willing to pull datasets directly from source systems
- Collaborate with development team for model integration into our existing analytics platform
- Grow and lead our quant team

**QUALIFICATIONS**

- M.S. or Ph.D in a technical discipline (mathematics, finance, physics, engineering or similar field)
- 3+ years of credit risk modeling experience (consumer loans experience preferred), with familiarity in major industry techniques, including multiple regression analyses, Markov modeling, and machine-learning
- Strong knowledge of mathematical finance and of numerical techniques employed in derivatives pricing models
- Hands-on implementation experience in Python (preferred), R, and/or MatLab, with familiarity in development best practices
- Highly collaborative, with facility working with other quants, developers, and product managers
- Great oral and written communication skills

**_Contact_:**

If interested, please email a short introduction and resume to

**careers@peeriq.com**.