Quantitative Researcher - Amsterdam

About this position

Quantitative Researcher - Amsterdam

Company description

• Radix Trading is a proprietary firm focused on quantitative research
• and scientific trading. We’re one of the most active liquidity
• providers on electronic exchanges globally, and have leveraged a
• culture of open, collaborative innovation to scale the reach of our
• ideas and pace of iteration, without having to scale our headcount. We
• operate in Chicago, New York, and Amsterdam.

• In our industry, the vast majority of ideas will fail. So, since
• inception, we’ve focused on continuous enhancement of our automated
• research platform and cutting-edge technology, allowing us to fail
• faster than the day prior, glean insights from each idea, and leverage
• individual contributions to the fullest across our entire
• organization.

We’re led by Ben Blander and Michael Rauchman.

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• Ben Blander - former head of Citadel’s high frequency group and a key
• contributor in growing their P&L from $75 million in 2005 to $1.15
• billion in 2008. Previously Ben earned a PhD in Math (Algebraic
• Topology under Peter May) from the University of Chicago.

• Michael Rauchman - formerly GETCO's CTO, head of Americas equities,
• and global head of ForEx. As a hands-on leader, Michael was
• instrumental in the development of many trading strategies as well as
• the underlying architecture and code.

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Why trading?

• If you want to get near-immediate feedback on your best ideas, while
• leveraging cutting-edge technology, the trading industry is hard to
• beat. Every day we’re competing with some of the smartest, most driven
• people in the world trying to take our money -- and if we don’t stay
• at the very top of our game in research, technology, and economics,
• they will.

• And while the highly-publicized wave of high-frequency or “flash”
• trading based on sheer speed of execution might have reached its
• limit, we see continued opportunities with our strategy of using
• statistical research to outsmart the competition.

Job description

• As a Quantitative Researcher, your focus is on identifying trading
• opportunities, but you can add even more value with strong
• quantitative skills and some coding proficiency to accelerate the
• innovation process and help others leverage your work.

• As you get going, you’ll gain new knowledge and insight into the
• fundamentals of market dynamics, trading strategies, and our
• proprietary research platform. We’ve stripped away the boundaries of
• what you can access and touch internally, so while you learn the
• intricacies of our industry, you’ll have plenty of opportunities to
• contribute and directly affect our bottom line within your first few
• weeks on the team.

• While interest in trading is key, a background in finance is
• definitely not. Our team is built mostly from academia — professors,
• postdocs, and PhDs — not from other trading firms. We seek mental
• diversity and add a select group of academics each year from a wide
• range of disciplines.

• COMPENSATION – Competitive salary, plus quarterly bonus based on
• individual performance and contribution towards success of others and
• the firm.

Qualifications

• We’re looking for highly analytical people (math, physics, computer
• science, statistics, electrical engineering, etc.) who want to help
• build the research-driven trading firm of the future. To do that,
• you’ll need the following qualities:

• > Persistent Drive to Improve - Do you have an innate desire to rise
• to the next level, even after great accomplishment? Our people have
• been very successful in their academic careers and are joining Radix
• to make even more impact.

• > Creative Problem Solving and Probabilistic Thinking - You must enjoy
• learning and implementing new concepts quickly, combining knowledge
• from different domains to create new ideas, and take a data-driven and
• probabilistic approach to testing and implementing new ideas.

• > Team Mindset - We want people who understand 1+1 > 2 and are as
• committed to making the team better through sharing ideas as they are
• driven to improve their individual performance.

• > Mental Flexibility & Self Awareness - You’ll have to frequently
• adapt based on new data, results, and feedback on your trading ideas
• and your performance.

• > Orientation for Making Money - Although we value academic training,
• our work is not an academic exercise. We take a hacker’s approach to
• testing ideas, dropping projects that consume time without high
• upside, and focusing our next efforts on what will create the most
• value for the firm.

Research / Quant trading strategy skills to have or develop

• > Strong intuition and deep thinking with data sets - Designs new
• alphas, understands complex systems; knows where to start, or ask
• others where to start

> Demonstrates strong “hacking” ability to quickly get into data to

look for empirical relationships and decipher noise or signal

• > Familiarity with classical statistical methods and knows when and
• how to apply them in a rigorous fashion; Easily learns how to apply
• new statistical methods; will seek out and learn new methods to better
• solve problems

> Experience with modern AI techniques and methods or desire to work

on Applied Machine Learning Problems

• > Constantly questions finance/trading data and stays motivated to
• seek answers despite most often proving that there is no correlation
• or signal

> Experience in setup of research framework and execution of projects

> Understanding of financial products, market dynamics, and

microstructure

• > Low-level computer languages like C++ or Python, Java, etc.;
• awareness of strength in particular language and ability to solve more
• complex problems due to understanding nuances of the language

• **We will eventually require 2+ academic recommendation letters, but these are not required to apply upfront. Preference for existing letters, at least 1 being from your advisor --- these should be framed for academic positions, scholarships, research grants etc ---- no need to have your references write something new