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For Companies At a Glance
- Tasks: Lead AI/ML initiatives to optimise business decisions and automate processes.
- Company: A top-tier financial institution at the forefront of technology.
- Benefits: Attractive salary, comprehensive benefits, and opportunities for professional growth.
- Why this job: Join a pioneering team and make a significant impact in financial services.
- Qualifications: PhD in a quantitative field with hands-on ML experience.
- Other info: Dynamic role with a blend of research and engineering in a collaborative environment.
The predicted salary is between 72000 - 108000 £ per year.
A leading financial institution seeks an Applied AI / ML Lead – Vice President - Machine Learning Engineer to harness AI techniques in its Commercial & Investment Bank. This role combines scientific research and software engineering, focusing on optimizing business decisions and automating processes.
Key responsibilities include:
- Building scalable Data Science capabilities
- Collaborating with engineering teams
- Deploying machine learning services
Candidates should hold a PhD in a quantitative field and have hands-on experience with machine learning models and MLOps tools.
VP, Applied AI/ML — Financial Services employer: Jpmorgan Chase & Co.
Contact Detail:
Jpmorgan Chase & Co. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land VP, Applied AI/ML — Financial Services
✨Tip Number 1
Network like a pro! Reach out to professionals in the financial services sector, especially those working with AI and ML. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Showcase your skills! Create a portfolio that highlights your hands-on experience with machine learning models and MLOps tools. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your research and engineering projects in detail, and don’t forget to highlight how you can optimise business decisions through AI techniques.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Make sure to tailor your application to showcase how your background aligns with the role of VP, Applied AI/ML in Financial Services.
We think you need these skills to ace VP, Applied AI/ML — Financial Services
Some tips for your application 🫡
Show Off Your Expertise: Make sure to highlight your PhD and any hands-on experience with machine learning models. We want to see how your background aligns with the role, so don’t hold back on showcasing your skills!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the VP, Applied AI/ML position. Use keywords from the job description to demonstrate that you understand what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see why you’re a great fit for the role!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your AI/ML Stuff
Make sure you brush up on the latest trends and techniques in AI and machine learning, especially those relevant to financial services. Be ready to discuss your hands-on experience with machine learning models and MLOps tools, as this will show that you’re not just theory but also practice.
✨Showcase Your Research Skills
Since this role combines scientific research with software engineering, prepare to talk about your PhD work and how it relates to real-world applications. Highlight any projects where you've optimised business decisions or automated processes using AI techniques.
✨Collaboration is Key
This position involves working closely with engineering teams, so be prepared to discuss your experience in collaborative environments. Share examples of how you’ve successfully partnered with others to build scalable data science capabilities.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company’s AI initiatives. Inquire about their current projects or challenges they face in deploying machine learning services, which will demonstrate your enthusiasm and strategic thinking.
