Data Scientist (Python, ML, SQL)

New Yesterday

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.
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.
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. 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
Rapidly prototype and industrialise advanced algorithms in Python, applying best-in-class practices such as strict typing, modular design, and automated testing.
Architect robust data cleaning pipelines and orchestrate workflows using tools such as Dagster within cloud-based CI/CD environments.
Partner with stakeholders to understand operational challenges, define use cases, and integrate data products into real-world business processes.
Mentor junior data scientists, championing excellence in coding, technical thinking, and agile collaboration.
A strong sense of ownership, with the ability to lead on complex problems from concept to production deployment.
A commitment to role modelling British Airways' leadership behaviours and brand values in everything you do.
A collaborative, pragmatic approach to working in cross-functional Agile squads.
Expert-level fluency in Python (required) with deep experience in ML, OR, and DS libraries (e.g. scikit-learn, pandas, numpy, Gurobi).
Strong knowledge of machine learning and optimisation techniques-including supervised, unsupervised learning, and operations research methods.
Solid background in software engineering for data science products: version control (Git), testing (unit, regression, E2E), CI/CD (GitHub Actions), and orchestration (Airflow, Dagster).
Proficient in SQL and cloud platforms (AWS preferred), with exposure to model/data versioning tools (e.g. A track record of delivering production-grade ML/optimisation solutions that create tangible business impact.
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).
~4-6 years working on production ML or optimisation software products at scale (required).
~ Experience developing industrialised data science software products (required).
~ 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.
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.
We encourage all those who work for us to consider opportunities right across our business to help you develop and progress.
Inclusion & Diversity
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.
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Location:
London
Job Type:
FullTime

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