Senior Portfolio Manager

We are looking for a seasoned Senior Portfolio Manager with a proven track record at established financial institutions. The ideal candidate has independently built, deployed, and operated quantitative trading strategies with reliable, verifiable returns across any major financial market - including equities, options, futures, forex, fixed income, or digital assets. Deep crypto expertise is not a prerequisite what matters is the rigour, discipline, and maturity of your approach to strategy development and risk management.

Key Responsibilities

. Lead quantitative research on market inefficiencies, liquidity dynamics, and price behaviour across one or more asset classes

. Design, evaluate, and continuously improve strategies, which may include:

Statistical arbitrage and mean-reversion strategies

Derivatives-based strategies including options, futures, and structured products

Trend-following, carry, or macro factor strategies in futures and forex

Market-making, liquidity provision, or funding-driven strategies

. Build and maintain robust backtesting infrastructure that accurately models execution costs, slippage, financing, and realistic fill assumptions

. Own live and paper-traded strategy operations end-to-end, including:

Real-time performance monitoring and risk tracking

Post-trade analysis and P&L attribution

Execution quality and slippage assessment

Identification of strategy failure modes and operational risks

. Iterate on strategies using live trading feedback and evolving market conditions to maintain return robustness over time

. Contribute to portfolio-level risk management including drawdown controls, capacity assessment, and cross-strategy correlation management

Required Qualifications

. Experience: 5+ years of relevant experience at established financial institutions - hedge funds, proprietary trading desks, asset managers, investment banks, or leading quant firms - with at least 3 years directly responsible for quantitative strategy research and live operations

. Track Record: Demonstrated history of independently building and operating quantitative strategies in live markets, with auditable or otherwise verifiable evidence of consistent, reliable returns

. Market Breadth: Solid working knowledge of at least one major financial market (equities, options, futures, forex, fixed income, or crypto)ability to apply transferable quant principles across asset classes is highly valued

. Programming: Strong Python proficiency with experience contributing to research or production trading codebases working knowledge o fa systems language such as C++ or Rust is a plus

. Execution Experience: Practical expertise in transaction cost management, slippage analysis, partial fill handling, and basic inventory or position risk control

. Quantitative Foundation: Solid grounding in probability, statistics, time-series analysis, and market microstructure theory experience working with high-frequency or tick-level market data

. Ownership Mindset: Able to independently drive well-scoped research projects to completion and collaborate effectively with developers and researchers in a lean team

What We Expect at This Level

. Drive the full strategy lifecycle: hypothesis backtest deployment support post-trade review

. Deeply understand - and actively close - the gap between backtest results and live performance

. Diagnose underperformance using execution data and market data, and propose actionable improvements

. Proactively identify strategy capacity decay as market regimes shift and develop mitigation plans

. Operate with high autonomy and full ownership in a high-trust, minimal-supervision environment

Nice to Have

. Hands-on experience independently operating live strategies, including incident response and risk intervention

. Familiarity with order-book-driven or event-driven backtesting system design and maintenance

. Background in options market-making, volatility trading, or derivatives structuring

. Experience with crypto market mechanics, including perpetual futures and funding rate dynamics

. Knowledge of portfolio construction, factor models, or systematic macro frameworks