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- Tasks: Create cutting-edge algorithms for real-time trading and risk management.
- Company: Join Goldman Sachs, a top global investment firm with a rich history since 1869.
- Benefits: Enjoy diverse opportunities, wellness programs, and a commitment to inclusion.
- Why this job: Be part of a dynamic team shaping the future of finance with innovative technology.
- Qualifications: Bachelor's in Computer Science, Math, or related fields; coding skills in Python, Java, or C++ required.
- Other info: Collaborate across teams to turn complex data into actionable trading strategies.
The predicted salary is between 43200 - 72000 £ per year.
Responsibilities :
- Design, build, and maintain complex, scalable, low-latency, 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 algorithms using statistical and mathematical approaches, developing new models to leverage trading capabilities.
- Work with large datasets to extract data and turn it into tradable information.
- Provide quantitative analysis, analyze noisy data, and generate ideas to build complex signals, incorporating theoretical physics and artificial intelligence to generate predictive models.
- Engineer software applications for high-frequency trading and develop logical theories for trade execution.
- Develop and implement feedback mechanisms to continuously improve model accuracy and effectiveness.
- Collaborate with cross-functional teams to understand business requirements and translate them into actionable solutions.
Requirements :
- Bachelor\’s degree in Computer Science, Operations Research, Math, Physics, or Statistics.
- Proficiency in programming languages such as Python, Java, or C++, with the ability to write efficient, clean, and maintainable code.
- Background in Probability, Statistics, Machine Learning, Natural Language Processing, Reinforcement Learning, or Large Language Models is desirable.
Additional Information :
About Goldman Sachs: At Goldman Sachs, we commit our people, capital, and ideas to help our clients, shareholders, and communities grow. Founded in 1869, we are a leading global investment banking, securities, and investment management firm headquartered in New York with offices worldwide.
We are committed to fostering diversity and inclusion, providing opportunities for professional and personal growth through training, benefits, wellness, and mindfulness programs. We are an equal opportunity employer and do not discriminate based on race, color, religion, sex, national origin, age, veteran status, disability, or other protected characteristics.
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Global Banking & Markets, Future Strats, Associate - London employer: Goldman Sachs, Inc.
Contact Detail:
Goldman Sachs, Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Global Banking & Markets, Future Strats, Associate - London
✨Tip Number 1
Familiarise yourself with the latest trends in algorithmic trading and quantitative finance. Understanding current market dynamics and technological advancements will help you engage in meaningful conversations during interviews.
✨Tip Number 2
Brush up on your programming skills, especially in Python, Java, or C++. Consider working on personal projects or contributing to open-source projects that showcase your ability to write efficient and maintainable code.
✨Tip Number 3
Network with professionals in the industry through platforms like LinkedIn or relevant meetups. Building connections can provide insights into the company culture at Goldman Sachs and may even lead to referrals.
✨Tip Number 4
Prepare for technical interviews by practising problem-solving with a focus on probability, statistics, and machine learning concepts. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with coding challenges.
We think you need these skills to ace Global Banking & Markets, Future Strats, Associate - London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in quantitative modelling, algorithmic trading, and programming languages like Python, Java, or C++. Emphasise any projects or roles that demonstrate your ability to work with large datasets and develop predictive models.
Craft a Strong Cover Letter: In your cover letter, express your passion for finance and technology. Discuss how your background in Computer Science, Math, or Physics aligns with the responsibilities of the role. Mention specific skills or experiences that make you a great fit for the position at Goldman Sachs.
Showcase Relevant Projects: If you have worked on projects involving machine learning, statistical analysis, or algorithm development, include these in your application. Provide brief descriptions of the projects, your role, and the outcomes to demonstrate your practical experience.
Highlight Collaboration Skills: Since the role involves working with cross-functional teams, mention any experiences where you collaborated with others to achieve a common goal. This could be through academic projects, internships, or previous jobs, showcasing your ability to translate business requirements into actionable solutions.
How to prepare for a job interview at Goldman Sachs, Inc.
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in programming languages like Python, Java, or C++. Bring examples of your past work that demonstrate your ability to write efficient and maintainable code, especially in the context of quantitative models or algorithmic trading.
✨Understand the Role's Requirements
Familiarise yourself with the responsibilities outlined in the job description. Be ready to explain how your background in Probability, Statistics, or Machine Learning aligns with the tasks you'll be handling, such as building trading algorithms or working with large datasets.
✨Prepare for Problem-Solving Questions
Expect to tackle complex, high-dimensional problems during the interview. Practice explaining your thought process when designing algorithms or models, and be ready to discuss how you would approach real-time trading challenges using statistical and mathematical methods.
✨Demonstrate Collaboration Skills
Since the role involves working with cross-functional teams, be prepared to share examples of how you've successfully collaborated in the past. Highlight your ability to translate business requirements into actionable solutions, showcasing your communication skills and teamwork.
