Global Banking & Markets, EM Structured Credit Desk Strat, Associate, London

Job title:

Global Banking & Markets, EM Structured Credit Desk Strat, Associate, London

Company

Goldman Sachs

Job description

Job Description:Emerging Markets Structured Credit Desk StratDo you have strong quantitative and analytical skills with a business mindset? We’re looking for a professional to join our team in London to work within the business to deliver tailored solutions to our clients.What we doThe Emerging Markets (EM) Strats team within the Global Banking and Markets (GBM) division is responsible for the modelling and pricing of Credit, FX and Rates products across EM underliers, as well as building risk management tools for the business and clients using cutting edge quantitative, machine learning, and other AI techniques. GBM’s core value is building strong relationships with our institutional clients, which include corporations, financial service providers, and fund managers. We help them buy and sell financial products, raise funding, and manage risk. The Strats team is a dynamic, entrepreneurial team with a passion for the markets, with individuals who thrive in fast-paced, changing environments and are energized by a bustling trading floor from where we operate within the business.Your ImpactThis role will focus on EM Structured Credit products, such as financing solutions to clients, as well as Structured Notes, but will expose you to the other asset classes by nature of the EM desk being cross-asset, allowing for growth opportunities.This presents a highly visible platform to use your skills and knowledge into making a direct impact for our clients and to the firm’s bottom line. This also provides an invaluable opportunity to build a deep foundation of product knowledge.Responsibilities

• Create new models or improve existing for structured products.
• Understand transaction risks and analyse drivers of profits and losses, for both new and existing transactions
• Drive commercial outcomes using data.
• Increase client market share via innovative tools and data analytics.

Qualifications

• Strong quantitative, analytical and coding skills with desire to develop commercial mindset
• Knowledge of Stochastic calculus and derivatives pricing, or Machine Learning background
• Solid work ethics, team oriented, high levels of motivation.
• Ability to work in fast-paced environment and time-sensitive situations.
• Effective communication skills in verbal and writing to both technical and business audience.
• Self-driven, quick learner, can-do attitude, always efficiently seeking effective solutions.

Preferred

• 2-4 years prior experience in a Quant role (in EM, or Structured Credit)
• MS, or PhD in Quantitative Finance, Maths, Physics, Engineering, or Computer Science

ABOUT GOLDMAN SACHSAt Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.We believe who you are makes you better at what you do. We’re committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers.We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html© The Goldman Sachs Group, Inc., 2023. All rights reserved.Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity

Expected salary

Location

London

Job date

Wed, 17 Jul 2024 06:35:38 GMT

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