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Kraken · 2 months ago

Sr. Quantitative Risk Manager - Liquidity

United States

Full-time

Remote

Senior Level

$127K/yr - $203K/yr

6+ years exp

Kraken is a mission-focused company rooted in crypto values, aiming to accelerate the global adoption of crypto. The Sr. Quantitative Risk Manager will design and maintain models to measure liquidity and funding stress, utilizing market and internal data to inform capital allocation and funding strategies.

BitcoinBlockchainCryptocurrencyEthereum

Growth Opportunities

Responsibilities

Design and maintain factor-based liquidity and funding stress models to measure the firm’s resilience under market and operational stress events

Integrate market and internal data (wallets, exchanges, counterparties, banking flows) into real-time capital and liquidity simulations

Develop and enhance Treasury’s quantitative model library, expanding from first-principles liquidity coverage and funding runoff analyses to advanced jump-diffusion, contagion, and regime-switching models as risk management matures

Partner with Treasury Product Engineering to deliver transparent, data-driven dashboards and stress visualizations through Kraken’s Capital Management Product

Perform sensitivity and factor attribution analysis, explaining how liquidity, counterparty, and funding dynamics impact overall growth capacity and balance-sheet deployment

Document, validate, and communicate models to senior leadership, risk committees, and external partners, ensuring consistency with governance and audit standards

Collaborate cross-functionally with Data, Product, and Finance to define data quality standards and align Treasury risk factors with enterprise metrics

Additional duties and responsibilities as assigned

Qualification

Liquidity risk modelingCapital risk modelingPython programmingSQLQuantitative analysisCollaborationCommunicationProblem-solving

Required

Bachelor's or Master's degree in a quantitative discipline (Finance, Financial Engineering, Applied Math, Physics, or related)

6–10 years of experience in treasury, liquidity risk, capital risk modeling, or market risk, preferably within a trading, fintech, or digital-asset environment

Strong Python programming skills (NumPy, Pandas, SciPy, Monte Carlo simulation engines) and working knowledge of SQL

Demonstrated experience building liquidity or funding stress test frameworks and factor-based capital models