Junior Quantitative Strategist
Jetstone Asset ManagementJetstone Asset Management is a quantitative trading and investment firm
Role: Junior Quantitative Strategist
Open posting date: 25 September 2020
Closing date for applications: 23 October 2020
Jetstone Asset Management
Jetstone Asset Management is a quantitative trading and investment firm with a focus on multi-asset class strategies. Founded in 2014, Jetstone manages approximately $1.5bn across a diverse set of fully automated portfolios deployed across exchanges globally.
Our mission is simple: Figure out how the world works - Uncover the causal relationships that drive global markets. We believe the economy is an emergent phenomenon that requires looking beyond rigid and dated assumptions to advance. To this end, we are committed to pushing the boundaries of applied statistics, machine learning and scientific computing, based on a holistic approach that combines deep domain expertise with advanced mathematical methods.
We place a strong emphasis on practical software development and data science skills. All candidates are expected to have expert knowledge of at least one scripting language (strong preference for Python) and basic experience with at least one compiled language (e.g. C/C++, Java, Scala, Go). Candidates must have proven experience contributing to medium- to large scale software or data science projects (open or closed source). They must have gone beyond pure academic knowledge in their respective domain and demonstrated a passion for building solutions independently from the ground up. All candidates should be comfortable with shell scripting, version control systems, common collaboration tools and development workflows. We are particularly keen to speak to candidates with an entrepreneurial drive, who have made contributions to open-source projects or have worked on other kinds of self-directed ventures in the past.
- PhD in statistics, computer science, physics or related STEM discipline from a top-tier university
- 0 - 3 years experience in a data science, software development or quantitative research role
- Strong foundational knowledge of mathematics, statistics, machine learning and scientific computing
- Working knowledge of supervised and unsupervised ML methods for regression and/or classification, and an understanding of their real-world advantages/disadvantages
- Sound understanding of applied Bayesian statistics and empirical game theory
- Fluent in Python and solid experience with the data science stack (numpy, scipy, pandas, sklearn, tensorflow, etc.)
- Experience with version control systems (Git), collaboration tools (issue trackers, shared repos, etc) and development workflows (CI/CD, automated testing, code reviews)
- Excellent communication skills, fluent in English
- Experience with a mainstream OO compiled language (e.g. C/C++, C#, Java)
- Finance domain knowledge in equities or futures
- Academic research experience with strong publication record