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- Tasks: Lead AI model development to transform financial workflows and enhance efficiency.
- Company: Join a forward-thinking company revolutionising finance with AI and investing in talent.
- Benefits: Enjoy a dynamic work environment that encourages innovation and personal growth.
- Why this job: Be at the forefront of AI in finance, driving strategic insights and competitive performance.
- Qualifications: Degree in relevant field; experience in finance and strong knowledge of machine learning required.
- Other info: Work closely with finance teams and data engineers to implement impactful AI solutions.
The predicted salary is between 43200 - 72000 £ per year.
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 (Milton Keynes)
Contact Detail:
Morgan McKinley (Milton Keynes) 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 current AI initiatives and financial processes. Tailoring your conversation to align with their goals will show that you are proactive and genuinely interested in contributing to their success.
We think you need these skills to ace AI Finance Lead
Some tips for your application 🫡
Understand the Role: Carefully read the job description for the AI Finance Lead position. Make sure you understand the key responsibilities and required qualifications, as this will help you tailor your application effectively.
Highlight Relevant Experience: In your CV and cover letter, emphasise your experience in finance-related roles and your familiarity with financial processes. Be specific about your achievements in AI and machine learning projects that relate to finance.
Showcase Technical Skills: Detail your technical proficiency in AI and machine learning techniques. Mention any relevant tools or programming languages you are familiar with, and provide examples of how you've applied these skills in previous roles.
Communicate Effectively: Demonstrate your excellent communication and stakeholder management skills in your application. Use clear and concise language, and ensure that your passion for integrating AI into finance comes through in your writing.
How to prepare for a job interview at Morgan McKinley (Milton Keynes)
✨Understand the Role
Make sure you thoroughly understand the responsibilities of the AI Finance Lead. Familiarise yourself with how AI can transform financial workflows and be ready to discuss specific examples of AI applications in finance.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning techniques and generative AI applications. Highlight any projects where you've successfully implemented AI solutions in finance, demonstrating your technical proficiency.
✨Communicate Effectively
Since this role involves working with various stakeholders, practice articulating complex AI concepts in simple terms. Be ready to explain how you would educate finance teams about AI capabilities and limitations.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills. Think of scenarios where you had to identify high-impact AI use cases or integrate AI models with existing systems, and prepare to discuss your approach and outcomes.
