Applied Quantitative Strategist

Trading Interview; New York (NY); On-site; USD 175,000 - 200,000; Full time

Job summary

Virtu is a leading financial firm known for leveraging cutting edge technology to deliver liquidity and innovative, transparent trading solutions. As a Quant at Virtu, you will join interdisciplinary teams of traders, quants and software engineers in a collaborative environment with exposure to global teams.

You will apply modern statistical methods to build predictive models, research new trading strategies, analyze existing ones, develop risk models, and create tools to automate research tasks

Qualifications

• PhD in Science, Math, Engineering or other quantitative or STEM programs.
• No previous Quant Finance or specific asset class experience required.
• Strong GPA and rigorous coursework.
• Exceptional quantitative, mathematical, and problem-solving skills.
• Excellent communication and collaboration abilities.
• Programming skills in Python and C/C++.
• Ability to solve technical and quantitative problems under pressure.
• Ability to express ideas mathematically and algorithmically.

Responsibilities

• Apply observation skills and modern statistical methods to identify and build predictive models.
• Research and implement new trading strategies.
• Analyze existing strategies to identify potential improvements.
• Develop risk models and frameworks to manage portfolio risks.
• Create tools to automate research tasks and improve visualization of complex data sets.

Skills

Python

C/C++

Education

PhD in Science/Math/Engineering

Tools

Python

C/C++

Job description

Virtu is a leading financial firm known for leveraging cutting edge technology to deliver liquidity and innovative, transparent trading solutions. As a Quant at Virtu, you will join interdisciplinary teams of traders, quants and software engineers in a collaborative environment with exposure to global teams.

You will apply modern statistical methods to build predictive models, research new trading strategies, analyze existing ones, develop risk models, and create tools to automate research tasks