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For Companies At a Glance
- Tasks: Lead the development of AI models to transform financial workflows and enhance efficiency.
- Company: Join a global business known for talent development and innovation in finance.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and creativity.
- Why this job: Be at the forefront of AI in finance, driving impactful change and strategic insights.
- Qualifications: Degree in relevant field; experience in finance and machine learning required.
- Other info: Work closely with finance teams and data engineers to implement cutting-edge solutions.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
Morgan McKinley is proud to be working in partnership with a global business to recruit an AI Finance Lead.
In this high-profile role, you will bring cutting-edge AI into finance. Working across Finance, AI, and IT, you'll deliver smart, scalable solutions that free your finance colleagues from manual tasks-enabling them to focus on strategic insights and drive competitive performance.
Role
Reporting to the Finance Director, you will lead the development and deployment of AI models that transform financial workflows. Your work will enhance efficiency and accuracy across functions like accounting, FP&A, treasury, tax.
Key Responsibilities for the AI Finance Lead;
- Design, build, and deploy AI and machine learning models to tackle complex financial challenges
- Support with wider finance teams to identify high-impact AI use cases across multiple finance domains
- Partner with data engineers to prepare and structure financial data for modelling
- Train, test, and fine-tune models, ensuring compliance and ethical standards
- Integrate AI models with IT and finance systems for streamlined, operational use
- Ensure interpretability and auditability of AI systems, adhering to financial regulation requirements
- Educate and support finance stakeholders in understanding AI capabilities and limitations
Profile
- Degree in a relevant field; advanced qualifications in AI (Machine Learning, Data Science, or Finance)
- Proven experience in finance-related roles and familiarity with financial processes
- Strong knowledge of machine learning techniques and generative AI applications
- Experience working with stakeholders to drive change and secure buy-in
- Excellent communication and stakeholder management skills
- Technical proficiency and proven delivery of projects from inception to implementation
- Creative and practical problem-solver with a hands-on delivery approach
The Company
With head offices in Northamptonshire the business is known for developing talent, investing in their people and welcoming new ideas. AI is revolutionising finance, shifting focus from manual, routine work toward analysis and decision-making. This role places you at the heart of that transformation-empowering finance teams and embedding AI across critical functions.
AI Finance Lead employer: Morgan McKinley
Contact Detail:
Morgan McKinley Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Finance Lead
✨Tip Number 1
Familiarise yourself with the latest trends in AI and finance. Understanding how AI is currently being applied in financial workflows will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Network with professionals in the finance and AI sectors. Attend industry events or webinars to connect with potential colleagues and learn about their experiences, which can provide valuable insights into the company culture and expectations.
✨Tip Number 3
Prepare to discuss specific AI projects you've worked on. Be ready to explain your role, the challenges faced, and the outcomes achieved, as this will showcase your hands-on experience and problem-solving skills.
✨Tip Number 4
Research the company’s approach to AI in finance. Understanding their current initiatives and how they integrate AI into their operations will allow you to tailor your discussions and show how you can contribute to their goals.
We think you need these skills to ace AI Finance Lead
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in finance and AI. Emphasise any projects where you've designed or deployed AI models, as well as your familiarity with financial processes.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about integrating AI into finance. Mention specific examples of how you've driven change in previous roles and how you can contribute to the company's goals.
Showcase Technical Skills: Clearly outline your technical proficiency in machine learning and data science. Include any relevant certifications or advanced qualifications that demonstrate your expertise in these areas.
Highlight Stakeholder Management: Discuss your experience working with stakeholders to secure buy-in for projects. Provide examples of how you've communicated complex AI concepts to non-technical audiences, showcasing your excellent communication skills.
How to prepare for a job interview at Morgan McKinley
✨Showcase Your AI Knowledge
Make sure to highlight your understanding of AI and machine learning techniques. Be prepared to discuss specific models you've worked with and how they can be applied to finance, as this role requires a strong technical foundation.
✨Demonstrate Financial Acumen
Since the position is focused on finance, it's crucial to demonstrate your familiarity with financial processes. Prepare examples of how you've previously tackled financial challenges using AI or data-driven solutions.
✨Prepare for Stakeholder Engagement
This role involves working closely with various stakeholders. Think of instances where you've successfully communicated complex ideas to non-technical audiences and how you secured buy-in for projects. This will show your ability to bridge the gap between finance and technology.
✨Emphasise Compliance and Ethics
Given the importance of compliance in finance, be ready to discuss how you ensure ethical standards in AI deployment. Share your thoughts on interpretability and auditability of AI systems, as these are key aspects of the role.
