Global Banking & Markets, Future Strats, Associate - London at Goldman Sachs
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

06 Sep, 25

Salary

0.0

Posted On

06 Jun, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Physics, Reinforcement Learning, Java, Probability, Python, Statistics, Natural Language Processing, C++, Computer Science, Machine Learning, Programming Languages

Industry

Information Technology/IT

Description

Futures Strats are responsible for all aspects of the futures electronic trading business, providing sophisticated execution-related services to the firm’s clients, with a particular focus on automated execution algorithms. They are responsible for market microstructure research, pre and post trade analytics as well as design, implementation, testing and support of high-performance algorithmic trading systems and strategies for the firm’s futures trading businesses. The team interfaces on a regular basis with clients, sales-trading, technology, and other Strats teams.

REQUIREMENTS:

  • A bachelor’s degree in Computer Science, Operations Research, Math, Physics or Statistics.
  • Proficiency in programming languages like Python, Java or C++ and the ability to write efficient, clean, and maintainable code.Background in Probability, Statistics, Machine Learning, Natural Language Processing, Reinforcement Learning, Large Language Models is desirable.
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Responsibilities
  • Design, build and maintain complex, scalable, low latency and high-capacity quantitative models for real time algorithmic trading, order state management, risk management, and other execution functions.
  • Design and implement novel trading algorithms and approaches to provide generalizable solutions to complex, high-dimensional problems, ensuring efficiency and scalability across different markets.
  • Build state of the art execution and market making algos using statistical and mathematical approaches and develop new models to leverage trading capabilities.
  • Work with super-large datasets to extract data and turn data into tradable information.
  • Provide quantitative analysis and analyze noisy data. Generate ideas to build complex signals and design overall strategies. Combine methods of theoretical physics and artificial intelligence to generate predictive mathematical models.
  • Engineer software applications for high frequency trading and develop logical theories for trade execution.
  • Develop and implement feedback mechanisms to continuously improve the accuracy and effectiveness of the models.
  • Communicate complex technical concepts and findings to non-technical stakeholders in a clear and concise manner.Collaborate with cross-functional teams to understand business requirements and translate them into actionable solutions.
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