Overview
Our client, located in central NJ, is an algorithmic hedge fund founded in 2003. They build robust, high-quality software that run and are managed on a global network of computer servers. Our software implements real-time mathematical models (using Machine Learning) that trade around the clock in many of the world’s financial markets and asset classes. Our client is a small group of scientists and software engineers who take pride in their software craftsmanship and are looking to add a Trading Operations Engineer to the team. Total compensation of 250k to 350k+ depending on experience. Compensation has never stood in the way of someone interested in this firm accepting a position.
Our client's culture has more in common with research laboratories and technology startups than with traditional finance. We prize curiosity, creativity, diligence, and intellectual honesty. We focus on the long term, working together to build elegant and general systems that endure and scale as we grow. And we incentivize our employees to cooperate and share ideas, because we know that compounding our efforts magnifies our achievements. The result is a company where smart, dedicated effort can have a major impact.
About the Job
Become a high-impact member of a small team at a rapidly growing firm.
Responsibilities:
Monitoring the health of the production trading system; diagnosing and fixing issues with intraday transactions and post-trade reconciliation.
Configuring and deploying changes to the trading system including new features, improvements, and fixes.
Working with infrastructure engineers on the development of automated configuration and deployment frameworks.
Working with peers to improve automation of operations.
Creating and improving operational tools for monitoring and collecting system health data.
Monitoring and supporting our proprietary trading infrastructure, including servers, operating systems, networks, colocation sites, and connectivity to numerous vendors and exchanges across the globe.
Monitoring market and portfolio risk, and interfacing with risk-analytics and research teams.
Qualifications:
A bachelor’s degree in computer science or engineering from a top university.
Exceptional problem-solving skills with the ability to act and think clearly during fast-paced, high-pressure situations.
Experience in a variety of technical competencies including Python, UNIX/Linux, SQL, and networking.
Strong interest in and exposure to financial markets.
Experience with trading infrastructure like the FIX protocol is a plus, but not required.