Quantitative Risk Modeling Analyst

Ready to be pushed beyond what you think you’re capable of?

At Coinbase, our mission is to increase economic freedom in the world.

To achieve our mission, we’re seeking a very specific candidate.

Our work culture is intense and isn’t for everyone.

Team / Role:

As part of Coinbase’s broader risk management organization, the Financial Risk Quant team is responsible for building quantitative models that assess and mitigate risks associated with our risk-bearing products, as well as measuring and monitoring portfolio exposures across the platform.

In this role, you will help design, develop, implement, and maintain a suite of financial risk models that form the foundation of our risk infrastructure.

What you’ll be doing (ie. job duties):

• Develop, implement, and maintain Potential Future Exposure (PFE) models across all risk-bearing products
• Design and calibrate margin models for exchange-traded and prime brokerage products
• Enhance and support the Value-at-Risk (VaR) model to monitor and manage market risk
• Develop, implement, and maintain liquidity models
• Write production level code for model implementation
• Conduct quantitative risk analyses to support risk-informed decision making, including limit setting, slippage analysis, and liquidation risk waterfall design
• Build and deploy quantitative tools within the firm’s risk platform
• Contribute to the development and implementation of liquidity and operational risk models as needed

What we look for in you (ie. job requirements):

• Phd or Master degree in a highly quantitative field.
• 2+ years of experience working in quantitative risk model development or quantitative research function within Investment Bank / Asset Management /Exchanges / Fintech.
• Familiar with the following financial products and understand the key risk factors associated with these products: asset backed lending, margin trading, prime brokerage services, exchange traded products.
• Have a deep understanding of different types of statistical and machine learning models/methodologies used in the financial industry: time series models, bayesian models, gaussian copula, multi-factor models, logistic/linear regression models, probit model, random forest, gradient boosting, etc.
• Have a good understanding of Monte Carlo Simulation and Brownie Motion in the financial industry setting.
• Understand the key credit risk and market risk assessment metrics and how to model these metrics: Potential Future Exposure, Probability of Default, Loss Given Default, Option Greeks, etc.
• Demonstrate proficiency in following programming skills: Python, SQL.
• Strong technical written skills for model documentation.
• Be able to communicate technical findings/issues clearly, especially to non-technical audiences.
• Strong willing to take the ownership and collaborate with others.

Nice to haves:

• Working exerience with derivatives (swaps, options, futures).
• Understanding of fundamentals of crypto assets and their protocols.
• Knowledge of liquidity risk models.

Job #: P70388

Pay Transparency Notice: Depending on your work {#location}, the target annual {#salary} for this position can range as detailed below.

Pay Range:

$152,405—$179,300 USD