AMD Private, Credit Strats, London, Associate at Goldman Sachs
London, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

05 Jun, 25

Salary

0.0

Posted On

05 Mar, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Financial Markets, Computer Science, Communication Skills, Mathematics, Python, Physics, C++, Finance, Financial Engineering, Statistical Concepts, Java

Industry

Financial Services

Description

JOB OVERVIEW:

The Quantitative Engineer will be responsible for the design, development, and implementation of quantitative models and algorithms for a financial services company. This individual will work closely with traders, portfolio managers, and other stakeholders to streamline reporting identify areas where quantitative analysis can provide insights and support decision-making.

QUALIFICATIONS:

  • Advanced degree in a related field such as Mathematics, Physics, Computer Science, Financial Engineering or a related field.
  • Strong programming skills in at least one language such as Python, C++ or Java
  • Strong understanding of mathematical and statistical concepts, especially in finance
  • Strong problem-solving skills and the ability to think critically
  • Excellent communication skills and the ability to work well in a team environment
  • Experience and interest in financial markets, risk management and portfolio management

EXPERIENCE:

  • Minimum of 2+ years of experience in a quantitative role in a financial services company
  • Background in equity or credit preferredFull stack development or Secdb/Slang experience preferred
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Responsibilities
  • Coverage all aspects of private business, with focus on validation, streamlining and reporting for illiquid and semi-liquid funds
  • Develop and implement quantitative models and algorithms to support trading and investment strategies
  • Conduct statistical and mathematical analysis of financial data to identify patterns and trends
  • Collaborate with traders, portfolio managers, and other stakeholders to identify areas where quantitative analysis can provide insights and support decision-making
  • Communicate results and findings to stakeholders in a clear and concise manner
  • Stay current with industry developments and new technologies
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