Quantitative Researcher

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🔥 4 minutes ago

🗽 New York – Remote

🗽 New York – Remote

💵 $150k - $200k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

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Engineers Gate

WebsiteLinkedInAll Job Openings

51 - 200 employees

Engineers Gate is a private trading firm based in New York City founded in early 2014. We are a team of mathematicians, computer scientists, financial engineers, and other market professionals managing private investment capital and building a next generation platform for quantitative trading. Through a systematic investment process, careful risk management, and a dedication to integrity, intellectual rigor, and collaboration, we seek to generate exceptional risk-adjusted investment returns. Engineers Gate is a Registered Investment Advisor regulated by the U.S. Securities and Exchange Commission as well as a Commodity Pool Operator regulated by the U.S. Commodity Futures Trading Commission.

📋 Description

• Driving and leading research initiatives under the guidance of a Portfolio Manager to enhance statistical arbitrage-based quantitative models • Developing advanced statistical and computational methods to work with massive data sets • Collaborating with the Project Manager and other team members to improve the existing research environment • Taking a proactive approach to problem-solving, demonstrating a high level of motivation and initiative in the pursuit of innovative trading strategies • Exploring new methodologies and approaches to stay at the forefront of quantitative finance • Staying informed about market trends, emerging technologies, and advancements in quantitative finance

🎯 Requirements

• Master's degree (US or Foreign Equivalent) in Financial Engineering or a related field • Two (2) years of experience in the job offered or in a related financial engineering role • Two (2) years of experience with statistical arbitrage in cash equities • Feature engineering techniques applicable to price predictions • Quantitative finance concepts, statistics, and financial markets • Mid-frequency alpha research • Customizing back testing algorithms • Machine Learning predictive models