At a Glance
- Tasks: Lead data science and AI initiatives to enhance airport operations at Heathrow.
- Company: Heathrow Airport, a global leader in aviation innovation.
- Benefits: Competitive salary, comprehensive benefits, and opportunities for professional growth.
- Other info: Join a team committed to responsible AI and sustainable practices.
- Why this job: Shape the future of AI in a dynamic environment that impacts millions.
- Qualifications: Proven experience in enterprise-scale data science and AI solutions.
The predicted salary is between 80000 - 100000 £ per year.
This role shapes how data science and AI are used across Heathrow. It sets direction for enterprise analytics and AI services that support safe, efficient and reliable airport operations. The role oversees Data Science and AI services across multiple business areas. It ensures AI use is responsible, well‑governed and delivers clear value. It also supports senior decision‑making through insight and evidence.
Responsibilities
- Set the direction for data science and AI across Heathrow, aligned to business needs.
- Put clear AI governance, ethics and assurance arrangements in place.
- Ensure analytics services are reliable, secure and meet agreed service outcomes.
- Oversee investment, supplier arrangements and value tracking for AI and analytics.
- Build sustainable capability across data science, AI engineering and analytics.
Qualifications
- Strong experience delivering data science or AI solutions at enterprise scale.
- Experience guiding teams that develop and deploy machine learning models.
- Practical knowledge of responsible AI, governance and regulatory expectations.
- Experience shaping strategy and turning insight into business outcomes.
- Experience using cloud platforms for analytics and AI workloads.
- Ability to explain technical ideas clearly to non‑technical audiences.
Desirable
- Experience working in complex operational environments.
- Familiarity with production‑level model deployment and monitoring approaches.
Head of Data Science and AI in London employer: Heathrow Airport
Heathrow Airport is an exceptional employer, offering a dynamic work environment where innovation in data science and AI directly contributes to enhancing airport operations. With a strong commitment to employee growth, we provide opportunities for professional development and the chance to work on impactful projects that ensure safe and efficient travel for millions. Our culture prioritises collaboration, ethical governance, and a focus on delivering clear value, making it a rewarding place to advance your career in a globally recognised setting.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Science and AI in London
✨Tip Number 1
Network like a pro! Reach out to people in the data science and AI field, especially those connected to Heathrow. Attend industry events or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Showcase your expertise! Create a portfolio that highlights your experience with data science and AI solutions. Include case studies of projects where you’ve shaped strategy and delivered business outcomes. This will help you stand out when you’re chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your ability to explain complex ideas simply. Since you’ll need to communicate with non-technical audiences, practice breaking down technical concepts into relatable terms. This will show you can bridge the gap between tech and business needs.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly shows your enthusiasm and commitment to joining our team at Heathrow. Let’s get you on board!
We think you need these skills to ace Head of Data Science and AI in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Head of Data Science and AI. Highlight your experience with enterprise-scale data science solutions and any relevant projects that showcase your ability to guide teams in deploying machine learning models.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain how your background aligns with the responsibilities outlined in the job description. Don’t forget to mention your understanding of AI governance and how you can contribute to responsible AI practices at Heathrow.
Showcase Your Communication Skills:Since you'll need to explain technical ideas to non-technical audiences, make sure to highlight examples where you've successfully done this in the past. We want to see how you can bridge the gap between complex data concepts and practical business outcomes.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates regarding your application status!
How to prepare for a job interview at Heathrow Airport
✨Know Your Data Science Stuff
Make sure you brush up on your data science and AI knowledge. Be ready to discuss your experience with enterprise-scale solutions and how you've guided teams in developing machine learning models. They’ll want to see that you can translate complex concepts into clear, actionable insights.
✨Showcase Your Governance Knowledge
Since this role involves ensuring responsible AI use, be prepared to talk about your understanding of AI governance and ethics. Have examples ready that demonstrate how you've implemented these principles in past projects, as well as how you’ve navigated regulatory expectations.
✨Align with Business Needs
Understand the business context of Heathrow and how data science can drive operational efficiency. Think about how you can align your strategies with their goals and be ready to share specific examples of how your insights have led to tangible business outcomes in previous roles.
✨Communicate Like a Pro
You’ll need to explain technical ideas to non-technical audiences, so practice simplifying complex topics. Use relatable analogies or examples from your past work to illustrate your points. This will show that you can bridge the gap between technical and business teams effectively.
