At a Glance
- Tasks: Develop and deploy machine learning models to enhance customer engagement and insights.
- Company: Join a dynamic team at IAG Loyalty, shaping rewarding experiences for customers.
- Benefits: Inclusive culture, growth opportunities, and a chance to work with cutting-edge data technologies.
- Why this job: Make a real impact by turning complex data into actionable insights that drive business success.
- Qualifications: Experience in machine learning, Python, SQL, and a passion for data-driven problem-solving.
- Other info: Embrace diversity and be part of a team that values your unique perspective.
The predicted salary is between 28800 - 48000 £ per year.
We are the people behind global loyalty currency, Avios, and home to two ambitious, growing businesses across Loyalty and Holidays. Each business has its own goals, strategy and team, but collectively we share a purpose to create the world's most rewarding experiences for our customers through loyalty programmes, new products and holidays.
We are 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 will work closely with stakeholders to uncover meaningful insights, build predictive models, and help shape the future of our data and machine learning capabilities.
You will 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 will 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 will 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 will 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.
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
Our vision, 'to create the world's most rewarding experiences,' applies not only to our customers but for our colleagues too. It’s about taking belonging seriously, actively fostering a culture where everyone feels welcomed and valued by embracing diverse identities, personal histories, and perspectives. This commitment makes IAG Loyalty a rewarding place to work and enhances our ability to solve complex problems, drive innovation, and better serve our customers and communities.
Please let us know if we can make any reasonable adjustments to support your interview process with us.
Data Scientist in London employer: IAG Loyalty
Contact Detail:
IAG Loyalty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or attend industry meetups. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Prepare for the interview by practising common data science questions. Get comfy with explaining your projects and how they relate to business outcomes. We want to see your passion for problem-solving!
✨Tip Number 3
Show off your skills with a portfolio! Create a GitHub repo showcasing your machine learning models and visualisations. This gives us a taste of what you can do and sets you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our team!
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let your enthusiasm for data science shine through! Share specific examples of projects you've worked on that highlight your skills in machine learning and data visualisation. We want to see how you can turn complex datasets into actionable insights!
Tailor Your Application: Make sure to customise your application to align with the job description. Highlight your experience with Python, SQL, and any relevant data science libraries. We love seeing candidates who understand our needs and can demonstrate how their background fits perfectly with our goals.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your experiences and achievements. We appreciate a well-structured application that makes it easy for us to see your qualifications and how you can contribute to our team.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our exciting journey of growth and transformation!
How to prepare for a job interview at IAG Loyalty
✨Know Your Data Science Stuff
Make sure you brush up on your machine learning models, especially classification, regression, and clustering. Be ready to discuss your experience with Python and libraries like pandas and scikit-learn, as well as how you've used SQL to query data. They’ll want to see that you can translate complex data into actionable insights.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've taken a business problem from ideation to solution. Think about specific projects where your analytical skills made a real impact. This is your chance to demonstrate how you can turn data into clear business outcomes, so have those stories ready!
✨Visualisation is Key
Since you'll be communicating insights to both technical and non-technical stakeholders, practice explaining your visualisations clearly. Bring examples of your work that showcase your ability to create compelling analytical outputs. Being able to communicate effectively is just as important as the data itself!
✨Embrace Curiosity and Adaptability
They’re looking for someone with a curious mindset who’s eager to learn and adapt. Be prepared to discuss how you stay updated with the latest trends in data science and machine learning. Show them that you’re proactive and ready to shift focus to where you can make the biggest impact!