Quantitative Trading Strategist

The Voleon Group•Berkeley, CA

1d•Onsite

About The Position

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future. Your colleagues will include internationally recognized experts in artificial intelligence and machine learning research as well as highly experienced finance and technology professionals. The people who shape our company come from other backgrounds, including concert music performances, humanitarian aid, opera singing, sports writing, and BMX racing. You will be part of a team that loves to succeed together. In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more. As a QTS, you will use deep markets knowledge alongside quantitative skills to improve the implementation of systematic trading strategies. Domains include improving algorithmic execution, securities lending, and portfolio financing across a variety of asset classes and markets. You will work at the intersection of trading and research on problems that require market domain expertise but also statistical and quantitative rigor.

Requirements

3+ years of experience in a quantitative trading environment with an emphasis on quantitative research
Bachelor’s degree in a scientific or quantitative discipline
Highly capable in python, R, and SQL; with the ability to write production level code and develop across teams
Proficient in basic statistics with an ability to apply valid statistical methods to judge outcomes from real-world data
Comprehensive understanding of market micro-structure and a passion for markets
Ability to effectively communicate across teams and present research findings in a clear and concise manner

Responsibilities

Measure and improve algorithmic execution quality across asset classes
Conduct high quality research across a variety of market related topics and asset classes.
Create relevant reports and present findings across teams
Write high-quality production level code.
Design and develop new packages, data pipelines and production trading applications
Collaborate with trading and RnD team members to improve our trading strategies
Provide domain expertise in market microstructure across asset classes to other members of trading and RnD
Manage relationships with external brokers and trading partners