Sr. Quantitative Risk Manager – Liquidity at Kraken

About Kraken

Kraken is a global crypto pioneer dedicated to accelerating the world’s transition to digital assets and financial freedom. With operations spanning 70+ countries and 50+ languages, the company has built a decade-long reputation for innovation, security, and transparency across the crypto ecosystem.

Kraken’s suite of products—including Kraken Pro, Wallet, Desktop, and Futures—empowers individuals, institutions, and developers to trade, invest, and build with confidence. Every Krakenite contributes to the company’s mission to make crypto accessible to all, through a culture rooted in integrity, optimism, and bold innovation.

About the Team

The Treasury and Capital Markets function within Kraken’s Finance organization is responsible for liquidity management, capital allocation, and financial resilience. The team combines quantitative analytics, risk modeling, and strategic insight to ensure Kraken operates with sufficient liquidity, stability, and scalability across market conditions.

This role sits at the intersection of quantitative finance, risk modeling, and data science, directly influencing Kraken’s ability to navigate volatility, fund growth, and protect capital.

Role Overview

The Sr. Quantitative Risk Manager – Liquidity will design and implement Kraken’s factor-based liquidity and funding stress-testing framework, forming the quantitative backbone of the firm’s Treasury risk and capital analytics.

You’ll transform on-chain, exchange, and internal financial data into actionable insights that shape real-time liquidity strategies, capital allocation, and balance-sheet optimization. This position requires a blend of quantitative modeling expertise, Python programming proficiency, and deep understanding of liquidity risk dynamics within digital-asset markets.

Key Responsibilities

• Design and maintain factor-based liquidity and funding stress models to evaluate firm resilience under market and operational stress scenarios.

• Integrate market, on-chain, and internal data into dynamic liquidity and capital simulations.

• Develop and expand Treasury’s quantitative model library, evolving from coverage and runoff analyses to advanced jump-diffusion and regime-switching models.

• Partner with Treasury Product Engineering to build real-time dashboards and visualization tools for liquidity and capital monitoring.

• Conduct factor attribution and sensitivity analysis, explaining liquidity, counterparty, and funding drivers impacting growth capacity.

• Document, validate, and present models to senior leadership, audit, and risk committees, ensuring compliance with governance standards.

• Collaborate with Finance, Data, and Product teams to align data integrity and model consistency across the enterprise.

Qualifications

• Bachelor’s or Master’s degree in a quantitative discipline (Finance, Financial Engineering, Applied Math, Physics, or similar).

• 6–10 years of experience in treasury, liquidity, or capital risk modeling, ideally within trading, fintech, or digital-asset sectors.

• Advanced proficiency in Python (NumPy, Pandas, SciPy, Monte Carlo simulation engines).

• Strong working knowledge of SQL and quantitative data integration pipelines.

• Proven ability to build and implement stress-testing frameworks for liquidity and funding risk.

• Excellent communication and documentation skills, with the ability to translate quantitative findings into strategic insight.