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We seek to be a long-term partner for institutional investors, developing investment solutions that meet clients’ needs through both commingled funds and customized portfolios. As principal investor with stable ownership and a long-term perspective, we take a patient approach in building businesses and investment programs and most importantly, we invest on our own behalf substantially in all our programs, offering clients a strong alignment in the quest of achieving attractive risk-adjusted returns.

Your role

The Quantitative Research Analyst is an integral member of our multiple award-winning direct Quantitative Macro Strategies team. The team focuses on delivering largely market neutral and diversifying streams of returns as well as negatively correlated and protective return profiles for a sophisticated, institutional investor base by investing across all asset classes and liquid markets traded globally. Under guidance of the Head of Research, the person is responsible for developing rule-based trading strategies as well as helping translate algorithms into code.

• Use rigorous scientific methodology and apply robust statistical analysis techniques to extract deep insights from extensive and varied financial markets data;
• Back test and implement trading models and signals in a systematic investing environment, accounting for changing macroeconomic conditions;
• Apply cutting-edge machine learning techniques and use unconventional data sources to drive innovation;
• Periodically update on research progress and prepare high-quality technical documentation of finalized strategies for submission to approval before releasing them into the trading system;
• Take personal ownership for and closely monitor the performance of your strategies in joint and mutual accountability with the portfolio managers and the head of risk management.

Requirements

• Masters or higher degree in Quantitative Finance, Econometrics, Mathematics, Statistics, Physics, Computer Science, or another highly quantitative field;
• Strong knowledge of probability theory and applied statistics (e.g. time-series forecasting, machine learning, pattern recognition, signals generation, features engineering);
• 2-3 years of work experience in a data driven research environment, preferably including using financial data (e.g., Bloomberg) at different time frames (e.g., daily, intraday, tick-by-tick);
• Experience with translating mathematical models and algorithms into production-ready code – strong knowledge of Python is a must; any other coding language (e.g., C#, C++, Java) is a plus;
• Experience in working with relational and non-relational databases;
• Genuine interest in financial markets is required. Prior experience in commodities or foreign exchange markets is a plus;
• Ability to abstract, research and think independently, argue open-mindedly and assertively, and above all else value the intense pursuit of excellence;
• Ability to manage multiple tasks and thrive in a fast-paced team environment;
• Excellent analytical and problem-solving skills, with strong attention to detail;
• Fluent verbal and written communication skills in English, other language skills helpful;
• Flexible, passionate and proactive team player, who is willing to go the extra mile

Location: Freienbach area, Switzerland (Nearby Zurich)

Status: 80-100%, Employment