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For Companies At a Glance
- Tasks: Drive AI and ML innovations, collaborating on cutting-edge projects in finance.
- Company: Join Goldman Sachs, a leading global investment firm with a dynamic culture.
- Benefits: Enjoy competitive salary, health insurance, fitness perks, and professional development opportunities.
- Why this job: Make a real impact by redefining AI in finance and tackling unique challenges.
- Qualifications: Master's or Ph.D. in relevant fields with hands-on AI/ML experience required.
- Other info: Be part of a diverse team with excellent career growth and networking opportunities.
The predicted salary is between 36000 - 60000 £ per year.
Opportunity Overview
Goldman Sachs is seeking an Applied AI Researcher to join our dynamic Applied Artificial Intelligence (AI) Research team. As an integral part of the team, you will play a pivotal role in driving the adoption of cutting‐edge AI and Machine Learning (ML) technologies at the firm.
In this role, you will have the opportunity to contribute to various AI/ML domains, including but not limited to machine learning, deep learning, natural language processing, information retrieval, time series analysis, and recommender systems. As an experienced AI Researcher, you will help address the unique challenges that arise in machine learning systems within the financial domain. Join us in redefining the boundaries of what’s possible in the intersection of quantitative research and artificial intelligence!
Your responsibilities will include:
- Collaborating effectively with colleagues to advance production machine‐learning systems and applications.
- Conceptualizing, experimenting with, and assessing AI/ML‐based software systems.
- Developing, testing, and maintaining high‐quality, production‐ready code.
- Demonstrating technical leadership by taking charge of cross‐team projects.
- Creating libraries and frameworks that underpin reliable and testable systems.
- Representing Goldman Sachs at conferences and within open‐source communities.
Required Qualifications:
- Strong hands‐on experience building and maintaining large‐scale Python applications.
- A Master’s or Ph.D. degree in Computer Science, Machine Learning, Mathematics, Statistics, Physics, Engineering, Quantitative Finance, or equivalent relevant industry experience.
- A minimum of 1‐3 years of AI/ML experience in the industry that demonstrates your expertise.
- Extensive experience in software development for quantitative investment workflows in equities, fixed income, or multi‐asset strategies.
At 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.
Applied Research - Artificial Intelligence - London - Associate London · United Kingdom · Associate employer: Goldman Sachs Bank AG
Contact Detail:
Goldman Sachs Bank AG Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Research - Artificial Intelligence - London - Associate London · United Kingdom · Associate
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with alumni from your university. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects. Whether it's GitHub repos or personal projects, having tangible evidence of your work can really set you apart during interviews.
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design questions. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with the types of problems you might face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in joining our team at Goldman Sachs.
We think you need these skills to ace Applied Research - Artificial Intelligence - London - Associate London · United Kingdom · Associate
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Applied Research role. Highlight your experience in AI/ML and how it aligns with what we do at Goldman Sachs. Show us why you're the perfect fit!
Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your skills in Python and machine learning. We love seeing real-world applications of your expertise, so don’t hold back!
Be Clear and Concise: Keep your application clear and to the point. Use straightforward language and avoid jargon unless it's relevant. We want to understand your experience without getting lost in technical terms.
Apply Through Our Website: Don’t forget to submit your application through our official website! It’s the best way to ensure it gets into the right hands. Plus, you’ll find all the details you need about the role there.
How to prepare for a job interview at Goldman Sachs Bank AG
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and machine learning concepts. Be ready to discuss your hands-on experience with Python applications and how you've tackled challenges in the financial domain. This is your chance to showcase your expertise!
✨Showcase Collaboration Skills
Goldman Sachs values teamwork, so be prepared to share examples of how you've collaborated effectively with colleagues on projects. Think about specific instances where your contributions helped advance production machine-learning systems or applications.
✨Demonstrate Technical Leadership
Highlight any experiences where you've taken charge of cross-team projects or led initiatives. Discuss how you conceptualised and assessed AI/ML-based software systems, as this will show your potential for technical leadership within the team.
✨Prepare for Problem-Solving Questions
Expect to face questions that test your problem-solving abilities, especially in the context of quantitative finance. Practice articulating your thought process when tackling complex engineering problems, and be ready to explain how you would approach real-world scenarios.
