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Book Portfolio Manager

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Offered by:

MCP (Switzerland) GmbH

Finance / Accounting
Zug

We are seeking candidates with senior quantitative portfolio management experience and intimate kledge of systematic strategiesJob Responsibilities (include, but not limited to the following)

  • Develop systematic strategies that use statistical signals associated with various market inefficiencies applied to a broad variety of asset classes including global equities and/or ETFs, futures, currencies and options
  • Lead, manage and grow a global equity quantitative investment portfolio
  • Deliver expertise in risk management and strategic portfolio optimization
  • Contribute to broader firm research and strategic initiatives

What You’ll Bring:

  • 15+ years’ proven expertise in quantitative investment management, developing systematic strategies for a Global portfolio, including a verifiable track record with positive PnL and Sharpe
  • Proficiency in designing and implementing algorithms, leveraging advanced data structures for optimal solutions and adept at applying statistical analysis to drive informed decision-making.
  • Comprehensive management experience, including successful leadership and mentorship developing junior portfolio managers.
  • Track record mentoring and developing statistical arbitrage research analysts
  • Strong programming skills in mainstream quant programming languages, including C, C++, and python

The Book Portfolio Manager Opportunity:

  • Transparent and formula-based compensation
  • Opportunities to contribute to other research and strategy initiatives
  • Access to WorldQuant’s alpha pool, portfolio management tools and innovative technology platforms
  • Access to a deep and broad menu of datasets supported by a dedicated data team
  • Cross-asset execution led by a multi-regional trading team
  • Participation in internal research conferences and forums
  • Autonomy to build your own strategies along with several opportunities for collaboration and mentorship
  • Access to AI and Machine Learning opportunities applied to financial markets