Product Manager (Risks)

New
J
JustMarketsFinancial Technology
EuropeFull-TimeMiddle
Salary not disclosed
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Job Details

Experience
3+ years
Required Skills
PythonSQLProduct ManagementClickhouseRisk Management

Requirements

  • 3+ years of Product Management experience in Risk Tech, Quantitative Trading, Crypto Derivatives Exchanges, or CFD Brokerages.
  • Deep knowledge of financial risk mechanics: Cross/Isolated Margin, Portfolio Margin, A/B/C-book operating models, Net Open Position (NOP) aggregation, and options risk metrics.
  • Solid understanding of low-latency backend architecture: lock-free concurrency, In-Memory data processing, IPC/Shared Memory, and financial protocols (FIX, WebSocket).
  • Strong understanding of market microstructure, order book dynamics (L2/L3), matching engine mechanics, and liquidity bridging/routing.
  • Mathematical rigor with the ability to translate complex abstractions into clear technical specifications.
  • Composure and decisiveness under pressure during high-volatility events.
  • Proficiency in Python/SQL for risk modeling (nice to have).
  • Experience with time-series databases like ClickHouse (nice to have).
  • Familiarity with low-latency languages like C++, Rust, or C# (nice to have).
  • Academic background in Quantitative Finance, Applied Mathematics, Computer Science, or Financial Engineering (nice to have).

Responsibilities

  • Drive the product vision, technical roadmap, and PRDs for key areas within the Risk Tech domain (Margin Engines, Exposure Management, Anti-Fraud, Derivatives Risk, Stress Testing).
  • Partner with Quants and the Head of Risk & Dealing to translate mathematical risk models (Monte Carlo, VaR, Volatility Surfaces) into deterministic algorithms for high-performance engineering teams.
  • Define edge-case handling rules for Black Swan scenarios, exchange de-pegging, and cascading liquidation events.
  • Collaborate with Dealing and Trading Ops teams to deliver high-performance internal admin tools, real-time risk monitors, and override APIs.
  • Conduct post-incident deep dives following major market movements to continuously optimize risk parameters and engine performance.
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