Systematic Macro Quantitative Researcher Job at Undisclosed, Santa Rosa, CA

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  • Undisclosed
  • Santa Rosa, CA

Job Description

Systematic Macro Quant Researcher | Multi-Strat Hedge Fund | San Francisco Bay Area

Our client, a globally established and highly prestigious multi-platform Hedge Fund, are seeking a Systematic Macro Quant Researcher to work with a new Portfolio Manager within their Systematic business. In this dynamic and collaborative role, you will be responsible for developing and implementing cutting-edge quantitative models and strategies across global macro futures markets (excluding commodities).

Key Responsibilities:

  • Quantitative Research & Strategy Development: Conduct rigorous quantitative research to identify market inefficiencies and develop systematic trading strategies. Utilize statistical, econometric, and machine learning techniques to model macroeconomic relationships and forecast asset prices.

  • Data Analysis & Signal Generation: Analyse large and complex datasets, including macroeconomic indicators, market prices, and alternative data sources, to extract predictive signals. Employ advanced data science methodologies to enhance the robustness and accuracy of models.

  • Model Implementation & Optimization: Collaborate with the technology and trading teams to build and implement quantitative infrastructure, models and strategies in a live trading environment. Continuously optimize and refine models to adapt to changing market conditions.

  • Risk Management: Work closely with risk management teams to assess and manage the risks associated with trading strategies. Develop risk models that account for various market scenarios and stress conditions.

Requirements:

  • 2-5 years’ experience in a high-performance trading environment, ideally on the buyside.

  • Experience of developing and implementing successful quantitative trading strategies, preferably within macro futures markets.

  • Advanced (Ph.D. or Master's) degree from a top-tier institution, in a quantitative discipline such as Economics, Finance, Mathematics, Statistics, Computer Science, or a related field.

  • Strong programming skills in Python, R, or a similar language, and the ability to write clean code.

  • Experience with statistical analysis, econometrics, and machine learning techniques.

  • Proficiency in working with large datasets and data analysis tools.

Due to demand, we are advertising this role anonymously. If you would prefer to speak to someone before submitting a CV, please send a blank application to the role and someone will be in touch to discuss. We can only respond to highly qualified candidates.

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