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- Tasks: Validate AI models, ensuring their performance and reliability while collaborating with developers.
- Company: Join Goldman Sachs, a leading global investment banking firm with a commitment to innovation.
- Benefits: Enjoy competitive pay, diverse opportunities, and a supportive work environment focused on growth.
- Why this job: Make a real impact in the world of AI and model risk management at a prestigious firm.
- Qualifications: Degree in a quantitative field and programming skills in Python are essential.
- Other info: Be part of a diverse team with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
Goldman Sachs's Model Risk Management (MRM) team plays a critical role in ensuring the safety and soundness of the firm's models. MRM validates a diverse set of models, including AI and machine learning models, used within the firm. This role offers the opportunity to significantly contribute to the firm's overall model risk management framework and AI.
The Model Risk Management (MRM) group is a multidisciplinary group of quantitative experts at Goldman Sachs with presence in New York, Dallas, London, Birmingham, Warsaw, Hong Kong, and Bangalore. The MRM group is responsible for independent oversight of Model Risk at the firm, ensuring compliance with Firmwide Policy on Model Control and related standards, including documentation to evidence effective challenge over the Model development, implementation, and usage of Models.
Responsibilities
- Independently validate the performance, accuracy, and reliability of AI models used within Goldman Sachs, focusing on aspects such as accuracy, explainability, model design, and algorithmic robustness.
- Develop and implement validation methodologies and benchmark models tailored to the specific characteristics of AI models.
- Conduct thorough testing and analysis of model outputs, identifying and documenting potential risks and limitations.
- Collaborate with model developers and business stakeholders to address identified issues and improve model performance.
Preferred Qualifications
- A Bachelor, Master or Ph.D. degree in Computer Science, Mathematics, Physics, Engineering, or a closely related quantitative field.
- Programming expertise in Python, including experience with relevant data science libraries (e.g., NumPy, Pandas, TensorFlow, Pytorch).
- Understanding of statistical modelling and machine learning algorithms.
- Excellent analytical, problem-solving, and communication skills.
- Demonstrated curiosity, ownership, and a willingness to work in a collaborative environment.
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.
We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process.
Risk, AI Model Validation, Vice President, Birmingham employer: Goldman Sachs
Contact Detail:
Goldman Sachs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Risk, AI Model Validation, Vice President, Birmingham
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at Goldman Sachs. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with recruiters or during interviews, make sure to highlight your programming expertise and any relevant projects you've worked on. Bring your AI model validation experience to the forefront!
✨Prepare for Technical Questions
Brush up on your knowledge of statistical modelling and machine learning algorithms. Be ready to discuss how you've tackled challenges in past roles, especially those related to model performance and accuracy.
✨Apply Through Our Website
Don't forget to apply directly through the Goldman Sachs careers page! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team.
We think you need these skills to ace Risk, AI Model Validation, Vice President, Birmingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the role. Highlight your programming expertise in Python and any relevant experience with AI models, as this will catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about model risk management and how your background makes you a great fit for the team at Goldman Sachs.
Showcase Your Analytical Skills: In your application, don’t forget to mention specific examples where you've demonstrated strong analytical and problem-solving skills. We love seeing how candidates have tackled challenges in the past!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at Goldman Sachs
✨Know Your Models Inside Out
Make sure you have a solid understanding of AI models, especially those relevant to the role. Brush up on your knowledge of model validation techniques and be ready to discuss how you would assess accuracy and robustness.
✨Showcase Your Programming Skills
Since programming in Python is key for this position, prepare to demonstrate your expertise. Bring examples of past projects where you've used libraries like NumPy or TensorFlow, and be ready to solve coding challenges during the interview.
✨Prepare for Analytical Questions
Expect questions that test your analytical thinking and problem-solving abilities. Practice articulating your thought process when tackling complex problems, as this will showcase your critical thinking skills to the interviewers.
✨Emphasise Collaboration and Communication
This role involves working closely with model developers and stakeholders. Be prepared to discuss your experience in collaborative environments and how you effectively communicate technical concepts to non-technical audiences.
