At a Glance
- Tasks: Lead the development of data science solutions that enhance decision-making across the airline.
- Company: Join British Airways, a pioneering airline with over 100 years of connecting Britain to the world.
- Benefits: Enjoy unlimited flight tickets, discounted fares, and opportunities for personal growth.
- Why this job: Make a real impact in aviation while working in a collaborative and innovative environment.
- Qualifications: Master’s degree or 6+ years of relevant experience in Data Science or related fields required.
- Other info: We value diversity and encourage applicants from all backgrounds to apply.
The predicted salary is between 48000 - 72000 £ per year.
A career without limits
As the nation’s flag carrier, we take great pride in connecting Britain with the world and the world with Britain.
It’s something we’ve been doing for over 100 years, ever since we launched the world’s first international scheduled air service between London and Paris.
This originality has been in our blood since day one. It’s the spirit we share with the people that fly with us, our partners, and our colleagues.
So, whether you are a reassuring voice on the end of a phone, a smile at the door, under a wing keeping the turbines spinning or landing us gently in far-flung places, a job at British Airways is yours to make.
We know great things can happen when you’re inspired to think big and bring your ambition to work every day, which is why, at British Airways the sky is never the limit.
The role:
Principal Data Scientist
Join British Airways as a Principal Data Scientist within our Operations Decision Support (ODS) team and play a key role in delivering transformative data science solutions at scale. As a full-stack technical lead within a product squad, you will design and implement the core algorithms and architecture that power decision-support products used across the airline. This is a high-impact role with end-to-end technical ownership over a full product codebase, blending deep technical expertise with strategic thinking to drive real business value.
What you’ll do:
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Own the technical delivery of core machine learning and optimisation modules within decision-support software products—ensuring seamless integration with our technical and business ecosystem.
- Collaborate with software engineering teams, product & change teams to turn their models into industrialized products that are used by the airline every day to make better decisions
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Rapidly prototype and industrialise advanced algorithms in Python, applying best-in-class practices such as strict typing, modular design, and automated testing.
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Architect robust data cleaning pipelines and orchestrate workflows using tools such as Dagster within cloud-based CI/CD environments.
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Drive key system design and modelling decisions—carefully balancing speed, scalability, technical complexity, and business value.
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Partner with stakeholders to understand operational challenges, define use cases, and integrate data products into real-world business processes.
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Lead analysis and visualisation to uncover opportunities, quantify value capture, and optimise feature delivery.
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Communicate clearly and credibly across teams, articulating modelling approaches, trade-offs, and results.
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Mentor junior data scientists, championing excellence in coding, technical thinking, and agile collaboration.
What you’ll bring to British Airways:
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A strong sense of ownership, with the ability to lead on complex problems from concept to production deployment.
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A mindset grounded in systems thinking and end-to-end product delivery.
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Adaptability and resilience in a fast-moving environment—embracing new challenges with a solution-oriented, can-do attitude.
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A commitment to role modelling British Airways’ leadership behaviours and brand values in everything you do.
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A collaborative, pragmatic approach to working in cross-functional Agile squads.
Your experience:
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Expert-level fluency in Python (required) with deep experience in ML, OR, and DS libraries (e.g. scikit-learn, pandas, numpy, Gurobi).
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Strong knowledge of machine learning and optimisation techniques—including supervised, unsupervised learning, and operations research methods.
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Solid background in software engineering for data science products: version control (Git), testing (unit, regression, E2E), CI/CD (GitHub Actions), and orchestration (Airflow, Dagster).
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Proficient in SQL and cloud platforms (AWS preferred), with exposure to model/data versioning tools (e.g. DVC), containerised solutions (Docker, ECS), and experiment tracking (e.g. MLflow).
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Demonstrated ability to frame business and technical problems, assess trade-offs, and select effective modelling approaches.
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Excellent communication skills and the ability to influence both technical and non-technical stakeholders.
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A track record of delivering production-grade ML/optimisation solutions that create tangible business impact.
Qualifications:
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Master’s degree or above in Data Science, Machine Learning, Operational Research or a related field, or 6+ years of highly relevant industry experience (required).
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4–6 years working on production ML or optimisation software products at scale (required).
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Experience developing industrialised data science software products (required).
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Domain knowledge in transport, operations, or network optimisation (preferred).
Are you ready to lead the future of data-powered decision-making at the heart of aviation? Apply now and take flight with British Airways.
What we offer:
We believe that all the people who work with us should feel valued for the part they play. It’s one of the reasons our rewards go far beyond a competitive salary.
From the day you join us, you’ll get access to brilliant staff travel benefits including unlimited basic and premium standby tickets on British Airways flights. You’ll also receive up to 30 discounted ‘Hotline’ airfares per year for yourself, friends, and family.
At British Airways you’ll have the chance to take on new challenges and move forward in a way that feels right for you. We encourage all those who work for us to consider opportunities right across our business to help you develop and progress.
We never stand still, and we don’t expect our people to either.
Inclusion & Diversity
At British Airways we all have a part to play in creating an inclusive place to work. Diverse representation among our people is really important to us and we recognise that all our colleagues are uniquely different and bring their own originality, creativity and identity to work.
Inclusion and diversity is a key driver of innovation and we’re committed to creating a culture where everyone feels that they can be themselves. We’re looking for people from all backgrounds and cultures to join us and be a part of our journey to become a Better BA as we continue to connect Britain with the world and the world with Britain.
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Principal Data Scientist employer: British Airways
Contact Detail:
British Airways Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Scientist
✨Tip Number 1
Familiarise yourself with British Airways' operations and decision-making processes. Understanding how data science integrates into their business model will help you articulate your insights during discussions.
✨Tip Number 2
Network with current or former employees of British Airways, especially those in data science roles. They can provide valuable insights into the company culture and expectations, which can be beneficial for your application.
✨Tip Number 3
Prepare to discuss specific projects where you've successfully implemented machine learning or optimisation solutions. Be ready to explain the impact of your work on business outcomes, as this aligns with the role's focus on delivering tangible value.
✨Tip Number 4
Showcase your leadership skills by highlighting experiences where you've mentored others or led projects. This is crucial for the Principal Data Scientist role, as they are expected to guide junior team members and drive technical excellence.
We think you need these skills to ace Principal Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, particularly with Python and machine learning. Emphasise any relevant projects or roles that demonstrate your ability to deliver production-grade solutions.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and how it aligns with British Airways' mission. Mention specific experiences that showcase your leadership in complex problem-solving and your collaborative approach in cross-functional teams.
Showcase Technical Skills: Clearly outline your technical skills related to the job description, such as your proficiency in Python, SQL, and cloud platforms. Provide examples of how you've used these skills in previous roles to drive business value.
Highlight Communication Abilities: Since the role requires clear communication across teams, include examples of how you've effectively communicated complex technical concepts to both technical and non-technical stakeholders in your application.
How to prepare for a job interview at British Airways
✨Showcase Your Technical Expertise
As a Principal Data Scientist, you'll need to demonstrate your expert-level fluency in Python and familiarity with machine learning libraries. Be prepared to discuss specific projects where you've applied these skills, focusing on the impact your work had on the business.
✨Communicate Clearly
Effective communication is key, especially when articulating complex modelling approaches to both technical and non-technical stakeholders. Practice explaining your past projects in simple terms, highlighting how your contributions led to tangible business outcomes.
✨Emphasise Collaboration
British Airways values a collaborative approach, so be ready to discuss your experience working in cross-functional Agile teams. Share examples of how you've partnered with software engineers and product teams to turn models into industrialised products.
✨Demonstrate Problem-Solving Skills
Highlight your ability to frame business and technical problems effectively. Prepare to discuss how you've assessed trade-offs in previous projects and the decision-making process you followed to select the most effective modelling approaches.