At a Glance
- Tasks: Lead AI strategy and drive innovation across the organisation.
- Company: Dynamic tech consultancy known for its innovative approach.
- Benefits: Competitive salary, full-time role, and opportunities for professional growth.
- Other info: Join a high-performing team in a fast-paced, evolving environment.
- Why this job: Shape the future of AI and make a real impact in a leading company.
- Qualifications: Proven experience in AI leadership and strong stakeholder management skills.
The predicted salary is between 81000 - 99000 £ per year.
Our client is seeking a strategic and experienced Head of AI to lead their artificial intelligence function and drive innovation across the organisation. This is a senior leadership role responsible for defining and executing AI strategy, delivering impactful solutions, and embedding AI capabilities into core business operations.
The successful candidate will bring a blend of technical depth, leadership capability, and commercial acumen, with a proven track record of delivering AI initiatives that create measurable value.
Key Responsibilities- Define AI Strategy: Develop and execute a clear AI roadmap aligned with the organisation’s broader business objectives.
- Lead AI Delivery: Oversee the full life cycle of AI and machine learning solutions, from ideation through to deployment and scaling.
- Team Leadership & Development: Lead, manage, and grow a high-performing AI team, driving a culture of innovation, accountability, and continuous improvement.
- Stakeholder Engagement: Partner with senior stakeholders to translate complex business challenges into effective, scalable AI solutions.
- Innovation & Emerging Technologies: Identify and leverage advancements in AI, including generative AI, large language models, and automation.
- Governance & Ethics: Ensure AI initiatives are delivered in line with best practices in ethics, compliance, and data governance.
- Commercial Impact: Drive tangible business outcomes, including efficiency gains, revenue growth, and enhanced customer experience.
- Proven experience leading and managing an AI or data science team
- Strong expertise in AI, machine learning, and advanced analytics
- Demonstrated experience delivering AI solutions within a commercial or enterprise environment
- Experience developing and implementing AI strategies at a senior level
- Excellent stakeholder management and communication skills
- Ability to translate technical concepts into business value
- Experience working with cloud platforms (e.g. Azure, AWS, GCP)
- Experience within, or in collaboration with, a Big 4 consultancy (Deloitte, PwC, EY, KPMG)
- Background in a consulting or client-facing environment
- Experience scaling AI capability within a growing or transforming organisation
- Familiarity with AI governance, risk, and regulatory frameworks
- A clearly defined and executed AI strategy aligned to business goals
- Successful delivery of scalable, production-ready AI solutions
- A high-performing, engaged AI team
- Measurable business impact driven through AI adoption
- The organisation is recognised as an innovator within its market.
Head of AI in Manchester employer: Hays
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StudySmarter Expert Advice🤫
We think this is how you could land Head of AI in Manchester
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Hays!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Head of AI at Hays.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Hays.
✨Apply Directly through Our Website
When you find a suitable opening like Head of AI at Hays, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Head of AI in Manchester
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Hays, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Hays. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Hays
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Hays!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
