At a Glance
- Tasks: Lead a talented Data Science team to solve complex business challenges using Machine Learning.
- Company: Join IAG Loyalty, a dynamic organisation transforming travel experiences.
- Benefits: Enjoy flexible hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborate across teams and embrace a culture of diversity and inclusion.
- Why this job: Make a real impact on customer engagement and profitability in a leading loyalty business.
- Qualifications: Proven experience in delivering Data Science solutions with strong Python and SQL skills.
We’re IAG Loyalty – one organisation with two ambitious, growing divisions across Loyalty and Holidays. Each has its own goals, strategy and team, but together we’re united by a shared vision to create a more rewarding world of travel and experiences. Our Loyalty division is home to Avios, the global loyalty currency, enabling millions of members to collect and spend rewards across travel, retail and financial services. Our Holidays division, including British Airways Holidays and Iberia Vacaciones, brings together trusted brands, connecting customers to thousands of destinations worldwide through seamless, end‑to‑end travel experiences. We’re on an exciting journey of growth and transformation.
The opportunity: Every Data Science team builds models. Ours is measured by the commercial value those models create. We’re looking for a commercially minded Data Science Lead to join our Data Products Leadership Team and help shape the future of Data Science across IAG Loyalty. This is an opportunity to lead a talented team whilst remaining hands‑on, solving some of our biggest customer, marketing and commercial challenges using Machine Learning and advanced analytics. Working across multiple product value streams, you'll partner with Product Owners, Engineers, Analysts and business leaders to identify where Data Science can create the greatest value, turning opportunities into production‑ready solutions that improve customer engagement, profitability and the way millions of members earn and spend Avios. Success in this role isn’t measured by the number of models you build. It’s measured by the business outcomes you create. You'll shape the Data Science roadmap, prioritise the highest‑value opportunities and ensure every solution delivers measurable commercial impact.
If you enjoy solving complex business problems, influencing strategy and developing high‑performing teams, this is an opportunity to make a real difference across one of the world’s leading loyalty businesses.
What you’ll be doing: As the Data Science Lead, you’ll combine technical leadership with commercial thinking, leading a team of Data Scientists whilst remaining hands‑on in the design and delivery of production‑ready Machine Learning solutions. Spending around half of your time on technical delivery, you’ll coach your team, set technical standards and ensure Data Science is focused on solving the business problems that matter most. Working closely with Product Owners, Analysts, Engineers and stakeholders across Commercial, Marketing, Customer, Finance and Digital, you’ll translate complex business challenges into high‑value Data Science use cases. You’ll build and prioritise a commercially driven backlog, balancing customer value, strategic priorities and technical complexity to ensure the team focuses on opportunities that deliver the greatest impact. Whether improving personalisation, recommendation systems, marketing effectiveness, pricing or customer lifetime value, you’ll ensure every solution has clear success measures and demonstrable commercial outcomes. Alongside delivery, you’ll champion experimentation, continuous learning and responsible AI, raising the technical bar across the Data Science community and helping shape the future direction of Data Science at IAG Loyalty. You’ll also play a key role as a member of the Data Products Leadership Team, influencing the direction of the function, developing future capability and ensuring Data Science continues to be recognised as a strategic driver of business growth.
What we need from you: You’ve successfully delivered Data Science solutions that created measurable commercial value, whether through increased revenue, customer engagement, profitability or operational efficiency. You naturally think about business outcomes first, using Data Science to solve customer and commercial challenges rather than simply building models. You’re comfortable working with ambiguity and can translate complex business questions into well‑defined, high‑value Data Science opportunities. You know how to prioritise work based on customer impact, commercial value and strategic importance, ensuring your team focuses on what matters most. You’ve successfully led, coached or mentored Data Scientists, creating an environment where people can learn, experiment and perform at their best. You’re an experienced hands‑on Data Scientist with strong Python and SQL skills and a track record of delivering production‑ready Machine Learning solutions. You have experience across customer, marketing or commercial Data Science, including recommendation systems, experimentation, pricing, propensity modelling, uplift modelling or similar use cases. You’re confident communicating complex technical concepts to both technical and non‑technical audiences, helping stakeholders understand both the solution and the commercial value it delivers. You enjoy working collaboratively with Product Owners, Engineers, Analysts and business stakeholders to solve meaningful problems. Experience with cloud‑based Machine Learning platforms, MLOps, LLMs or Agentic AI is advantageous, although we’re more interested in your ability to learn quickly and apply new technologies to solve business problems.
We might not be right for you if: You only want to focus on your to-do list; we’re a small, high‑performing team and we help each other to succeed. You value perfection over fast iteration and progress; IAG Loyalty moves fast, we learn and iterate as we go, and our environment isn’t right for everyone. You’re looking to build models without understanding the commercial outcome; this is an end‑to‑end leadership role where you’ll shape strategy, prioritise opportunities and measure the value your team delivers. You’re looking to create but not build; you’ll need to be comfortable owning your space from identifying opportunities through to delivery, measurement and continuous optimisation.
The Blend: This role will work as part of our Loyalty Division and is based in our London office. We call our approach to hybrid working The Blend – it’s about giving you the flexibility to choose where you do your best work, while staying connected with your team and the wider business. This means you’ll be required to spend at least two days per week in the office, with the rest of the time working from home. Although this role sits within our Loyalty Division, you’ll collaborate with colleagues across both Loyalty and Holidays, using data and AI to help create more rewarding travel experiences for millions of customers. You may also be required to work from one of our other office or partner locations, depending on business needs and your priorities.
Diversity and Inclusion: Our vision is to create a more rewarding world of travel and experiences. Delivering that requires diverse thinking and inclusive leadership. We are committed to building a workplace where people feel they belong and are valued for their perspective. Inclusion drives better decisions, stronger performance and more innovative outcomes. We actively encourage applications from people with different experiences and backgrounds, and are committed to ensuring our recruitment process is fair, inclusive and accessible.
Data Science Lead employer: IAG Loyalty
IAG Loyalty is an exceptional employer, offering a dynamic work environment in Crawley where innovation and collaboration thrive. With a strong commitment to employee growth, we provide ample opportunities for professional development and leadership training, ensuring that our team members can shape their careers while contributing to a diverse holiday portfolio. Our inclusive culture fosters creativity and teamwork, making IAG Loyalty a rewarding place to work for those seeking meaningful impact in the travel industry.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead
✨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 IAG Loyalty!
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✨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 IAG Loyalty.
✨Apply Directly through Our Website
When you find a suitable opening like Data Science Lead at IAG Loyalty, 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 Data Science Lead
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 IAG Loyalty, 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 IAG Loyalty. 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 IAG Loyalty
✨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 IAG Loyalty!
✨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.