Fasanara Capital
Fasanara Capital is a boutique alternative asset manager, offering access to a range of inventive multi-asset capacity-constrained niche products. Over the past 10 years, we are pursuing unorthodox portfolio construction and unconventional investment strategy is a response to today’s transformational markets.
Fasanara Digital was established 4 years ago and is the crypto arm of Fasanara Capital. We are a quantitative investment fund applying a scientific approach to investing in cryptoassets. Our goal is to achieve exceptional risk-adjusted returns. We pursue a range of diversified and highly sophisticated investment strategies that seek to profit from inefficiencies in the market structure.
Our Culture
We are strong believers in meritocracy, and we seek to reward people based on impact and excellence. There is no bureaucracy of large organisations, the environment is collaborative, entrepreneurial, and is based on trust. We set ambitious goals, work extremely hard, stress teamwork, and adhere to the highest level of excellence in everything we do. We are only as good as our team. Thus, we are building the firm around exceptional talent.
The Position
We are looking for a Quant Strategist Intern who will be part of a small team directly working with portfolio managers. In the role, you will be researching, designing, and implementing new trading strategies as well as improving the existing ones. Responsibilities also include monitoring trading activities to ensure the efficacy of models.
Responsibilities:
- Design and implementation of data acquisition and processing tools, both real-time and offline
- Research analytics for trading signal generation, optimisation of execution, and portfolio construction in conjunction with portfolio managers
- Enhancement of operational efficiency through automation
- Risk monitoring, alerting and position, and P&L calculation
Requirements:
- Advanced degree in a highly quantitative discipline
- Experience of applying advanced quantitative techniques in solving complex data-intensive problems
- Strong analytical skills and excellent familiarity with data analysis in Python
- Hands-on experience with large volumes of time-series data & time-series databases
- Familiarity with SQL
To apply for this job please visit www.linkedin.com.