Who we are 🌍
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 – we’re going places.
The opportunity ✨
We’re looking for a Data Scientist with a few years of industry experience to join our team working on customer data. This role is ideal for someone who enjoys combining hands-on machine learning with exploratory analysis, data visualisation, and business problem-solving.
You’ll work closely with stakeholders to uncover meaningful insights, build predictive models, and help shape the future of our data and machine learning capabilities. Through a strong understanding of customer data and business needs, you’ll turn complex datasets into clear, actionable insights that support decision-making and drive impact.
This is an opportunity to apply data science in a practical, outcomes-focused environment, where your work directly influences how data and ML are used to solve real business problems and create value.
What you’ll be doing 🚀
You’ll develop, evaluate and deploy machine learning models to support customer engagement, retention, churn prediction, and cross-sell and up-sell use cases. Alongside this, you’ll create clear and compelling visualisations and analytical outputs to communicate insights effectively to both technical and non-technical stakeholders. Your work will span a range of projects, from hands-on data science and modelling to more analytical and self-serve initiatives.
You’ll work closely with engineers, analysts and business teams to translate business questions into practical data solutions, while maintaining high standards of data quality, validation and documentation throughout the delivery lifecycle. You’ll also contribute to improving data science best practice, tooling and ways of working, and show a strong interest in developing your machine learning engineering skills, including model deployment, monitoring and scalability.
What we need from you ⚡
We are aiming high, and we accept that it is unlikely that any one person will meet every aspect of the brief. Who you are is equally as important as what you have done or where you have worked.
So even if you don't tick every box, or your experience is from a unique or varied background, we'd still love to hear from you!
Strong experience developing and evaluating machine learning models (e.g. classification, regression and clustering), with a solid grounding in statistical techniques
Proficient in Python and common data science libraries such as pandas and scikit-learn
Experience working with structured data, ideally customer or transactional datasets
Confident using SQL to query data and working with data warehouses
Able to take problems from initial ideation through to solutions that deliver clear business outcomes
Comfortable working across modelling, analysis and data visualisation
Familiar with cloud platforms and data pipelines
Highly analytical, with a focus on improving customer interactions through data
Strong attention to detail and a clear commitment to data quality
Proactive, adaptable and comfortable shifting focus to where the greatest impact can be made
Curious mindset with a genuine desire to learn, improve and develop over time
Interest in growing towards a more machine learning engineering–focused skill set
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, 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; our environment isn’t right for everyone.
You’re looking to create but not build; this is an end-to-end role, you need to be comfortable owning your space, from ideation through to delivery and review.
If you think you have what it takes but don't meet every single point above, please do still apply. We'd love to chat and see if you could be a great fit.
This role will work as part of our Loyalty Division and is based out of 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 will be required to spend at least two days per week in the office, with the rest of the time working from home. You may also be required to work from one of our other office or partner locations, based on your role and 'to do' list
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.
Top Skills
IAG Loyalty London, England Office
123 Buckingham Palace Road, London, United Kingdom, SW1W 9SH
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