Quant Risk

Job not on LinkedIn

🕒 April 30

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

SwissBorg

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2017

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

SwissBorg is a leading cryptocurrency investment platform in Europe, offering a secure and reliable app for buying, selling, and exchanging cryptocurrencies. It provides exposure to decentralized finance (DeFi) through a curated portfolio that evolves with expert market insights. The platform supports multiple fiat currencies, including EUR, CHF, and GBP, and is licensed and regulated, ensuring the safety and accessibility of users' funds. With innovative features like Thematics, Smart Engine, and Portfolio Analytics, SwissBorg empowers users to make informed investment decisions, diversify their crypto holdings, and earn passive income with minimal risk. SwissBorg also offers its own multi-utility token, BORG, for community participation and investment within its ecosystem.

📋 Description

• Support and enhance the real-time risk engine processing 10k+ position updates/second across perpetuals, spots, and prediction markets. • Design and implement risk metrics: portfolio VaR, stress VaR, expected shortfall, Greeks aggregation, cross-asset correlations. • Build position limit frameworks: notional caps, delta limits, concentration limits, leverage constraints, drawdown thresholds. • Develop statistical models for tail-risk scenarios: fat-tailed distributions, regime switching, correlation breakdowns. • Implement margin calculation engines: cross-margining logic, liquidation price models, maintenance margin monitoring. • Work closely with trading infrastructure team to ensure <50ms P99 latency for risk calculations on critical paths. • Create real-time dashboards and alerting systems: exposure heatmaps, PnL attribution, limit breaches, anomaly detection. • Backtest risk models against historical liquidation events and high-volatility periods to validate accuracy. • Design circuit breakers and kill switches for extreme market conditions or system anomalies.

🎯 Requirements

• 3+ years of experience in quantitative risk, trading systems, or financial engineering. • Strong foundation in statistics, probability theory, and risk modeling (VaR, CVaR, ES, stress testing). • Proficiency in Python with NumPy, Pandas, SciPy for quantitative analysis and backtesting. • Experience with real-time risk systems processing 1000+ updates/second with <50ms latency. • Deep understanding of derivatives pricing: perpetual funding rates, mark-to-market, liquidation mechanics. • Portfolio risk metrics: Greeks (delta, gamma, vega), correlation matrices, beta hedging, tail risk. • Experience with crypto perpetuals (funding rates, cross-margining, liquidation cascades). • Familiarity with prediction markets (AMM mechanics, Kelly criterion, order book dynamics). • Time-series analysis: volatility modeling (GARCH, EWMA), regime detection, autocorrelation. • SQL proficiency for risk aggregation queries across millions of position updates. • Ability to translate complex risk concepts into real-time monitoring systems. • Understanding of margin calculations, position sizing, and drawdown controls.

🏖️ Benefits

• Health insurance • Competitive salary • Flexible work hours • Professional development opportunities