[Remote] Quantitative Risk Modeling Manager
Note: The job is a remote job and is open to candidates in USA. Coinbase is a company on a mission to increase economic freedom in the world, seeking a passionate candidate to join their team. The role involves leading the design of Coinbase’s next-generation Global Liquidation Engine, managing risk, and building algorithms for liquidating distressed portfolios.
Responsibilities
- Design Optimal Liquidation Logic: Develop stochastic control models (adapting Almgren-Chriss frameworks) to determine the optimal trajectory for unwinding distressed portfolios. You must solve for the trade-off between market risk (holding the position too long) and market impact (selling too fast and crashing the price)
- Global Optimization: Move beyond single-client liquidation. Build logic that optimizes risk at the aggregated level —managing multiple concurrent liquidations to minimize total market impact and maximize liquidity usage across various venues
- Build 'Crisis-Ready' Algos: Adapt standard execution benchmarks (VWAP, POV, Implementation Shortfall) for stressed regimes where liquidity evaporates and spreads widen
- Portfolio-Level Unwinds: Develop logic to liquidate based on risk sensitivities ( Greeks ) rather than just line items (e.g., •"Don't just sell the spot asset; buy the put options to flatten the Delta first"•)
- Design and tune the decision logic for the liquidation lifecycle: Open Market Liquidation (smart order routing and order book interaction). Internalization / Hedging (Delta-neutralizing the portfolio internally). Private Auctions (soliciting bids from liquidity providers)
- Liquidity Intelligence: Collaborate with Exchange Liquidity Managers to estimate order market impact and monitor L1-L3 order book dynamics
- Regulatory Defense: Ensure all liquidation logic meets the "Commercially Reasonable" standard. Produce quantitative evidence and backtesting results to justify execution decisions to regulators and institutional clients
Skills
- Ph.D. or Master's degree in a highly quantitative field (Physics, Mathematics, Statistics, Financial Engineering, or Computer Science)
- 6+ years of relevant experience with a Ph.D from a top program
- 8+ years of relevant experience with a Master's degree
- Experience in one of the following hybrid areas: Central Risk Book (CRB) execution trading quant at a Tier 1 Investment Bank, Default Management risk quant at a major Clearing House (CCP) or Prime Broker, Electronic Market Making with a specific focus on inventory management, liquidation, or risk constraints
- Deep understanding of Almgren-Chriss frameworks, Order Book Dynamics (L1-L3 data), and Auction Theory
- Experience with Cross-Margining methodologies and models (e.g., offsetting Crypto futures against Spot, or Equity Options against Index futures)
- Production-level proficiency in Python
- Experience deploying quantitative models into production environments and integrating with execution APIs
- Proven ability to lead cross-functional projects (Product, Eng, Data Science) and communicate complex technical findings to non-technical stakeholders
- Hands-on experience modeling both Delta-One (Spot/Futures) and Non-Linear (Options/Vol) products
- Familiarity with modern data pipelines (e.g., Airflow) and real-time data streaming architectures (e.g., Kafka)
- Understanding of specific nuances in crypto market structure (24/7 trading, fragmented liquidity, on-chain vs. off-chain settlement)
Benefits
- Medical
- Dental
- Vision
- 401(k)
Company Overview
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