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For Companies At a Glance
- Tasks: Validate AI models, ensuring accuracy and compliance while collaborating with experts.
- Company: Join Goldman Sachs, a leading global investment banking firm with a diverse culture.
- Benefits: Enjoy competitive salary, wellness programs, and opportunities for professional growth.
- Why this job: Make a real impact in AI model validation at a top financial institution.
- Qualifications: Degree in a quantitative field and programming skills in Python required.
- Other info: Dynamic team environment with excellent career advancement opportunities.
The predicted salary is between 43200 - 72000 £ per year.
About the Team
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.
MODEL RISK MANAGEMENT (MRM)
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. The group’s primary mandate is to manage risk that arises from models used in the firm through its range of businesses - from models used for derivatives valuation to models used for risk management, liquidity and capital computations. In addition to independently reviewing these classes of models for their validity, theoretical consistency and implementation accuracy, the group is also responsible to assess the risk associated with model choice, e.g., exposure to choice of model in various contexts such as pricing exotic options or in calculating capital.
Who We Look For
Goldman Sachs is seeking a highly motivated AI Model Risk VP to join our Model Risk Management (MRM) team in Birmingham. You will play a crucial role in validating the firm's AI models, ensuring their accuracy, reliability, and compliance with regulatory requirements. This is a unique opportunity to gain exposure to a wide range of AI applications within a leading global financial institution and contribute directly to the firm's risk management framework. You will work closely with AI researchers, AI model developers, and other stakeholders to understand model methodologies, assess model risks, and implement validation plans and benchmarking 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.
About Goldman Sachs
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, Associate/Vice President, Birmingham employer: WeAreTechWomen
Contact Detail:
WeAreTechWomen Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Risk, AI Model Validation, Associate/Vice President, Birmingham
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Goldman Sachs, especially in the MRM team. A friendly chat can give us insider info and might even lead to a referral.
✨Tip Number 2
Prepare for those interviews by brushing up on your AI model validation knowledge. We should be ready to discuss specific methodologies and our experience with Python libraries. Practice makes perfect!
✨Tip Number 3
Showcase our passion for AI and risk management during interviews. Share examples of how we've tackled challenges in previous roles. This will help us stand out as candidates who are genuinely interested in the field.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure our application gets seen by the right people. Plus, it shows we’re serious about joining the Goldman Sachs team.
We think you need these skills to ace Risk, AI Model Validation, Associate/Vice President, Birmingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role you're applying for. Highlight your experience with AI models and risk management, as these are key areas for us at Goldman Sachs. We want to see how your skills align with our needs!
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 our team. We love seeing genuine enthusiasm!
Showcase Your Technical Skills: Don’t forget to highlight your programming expertise, especially in Python and relevant libraries. We’re looking for candidates who can demonstrate their technical prowess, so make sure to include specific examples of your work.
Apply Through Our Website: We encourage you to apply through our website for the best chance of being noticed. It’s the easiest way for us to keep track of your application and ensure it gets to the right people. Good luck!
How to prepare for a job interview at WeAreTechWomen
✨Know Your Models Inside Out
Make sure you have a solid understanding of the AI models you'll be validating. Brush up on their methodologies, strengths, and weaknesses. Being able to discuss specific examples of model performance and potential risks will show your expertise and readiness for the role.
✨Showcase Your Technical Skills
Since programming in Python is crucial for this position, be prepared to demonstrate your coding skills. Bring along examples of projects you've worked on using libraries like NumPy or TensorFlow. This will not only highlight your technical abilities but also your hands-on experience with relevant tools.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about how you would approach validating a new AI model or addressing a specific risk. Practising these scenarios can help you articulate your thought process clearly during the interview.
✨Emphasise Collaboration and Communication
This role involves working closely with various stakeholders, so be ready to discuss your experience in collaborative environments. Highlight instances where you've effectively communicated complex ideas to non-technical team members, as this will demonstrate your ability to bridge gaps between technical and business perspectives.
