Lead Product Data Scientist

British Airways
Hounslow
1 day ago
Create job alert
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

Lead Product Data Scientist

As Lead Product Data Scientist, you will lead a full‑stack data science and software engineering product squad to deliver optimisation and machine‑learning decision‑support products for an operational business area, aligned to the integrated operations vision.

This is a hands‑on leadership role. You will own the end‑to‑end product lifecycle from discovery and scoping through to architecture, delivery, testing, adoption, value capture and ongoing support. You will be expected to bring strong technical depth and practical experience with modern data science and software engineering tooling to guide delivery decisions and ensure production‑ready outcomes.

What you’ll do
  • Lead the end‑to‑end product development process for machine learning and optimisation products, from discovery to live operation and support
  • Understand business problems and end‑to‑end processes to identify opportunities to improve decisions using decision‑support tooling
  • Design modelling approaches and software architecture that are scalable, maintainable and aligned to the integrated operations vision
  • Create delivery timelines and feature roadmaps prioritised by business value, managing internal and external dependencies
  • Communicate product vision and secure alignment with senior stakeholders and business users
  • Ensure timely delivery of features, modules and the overall codebase across a cross‑functional squad
  • Define testing and validation approaches for individual features and end‑to‑end systems, with a focus on robustness and value capture
  • Lead regular internal and stakeholder sessions to drive modelling decisions and delivery predictability
  • Lead change management including communications, training and engagement to ensure adoption and realised value
  • Own product management including user experience and front‑end design considerations
  • Provide product support including bug fixing and coordination with dependent teams
  • Embed effective agile ways of working including version control, code reviews, documentation and continuous improvement
What you’ll bring to British Airways
  • Strong hands‑on experience applying machine learning and optimisation techniques to real‑world problems
  • Deep technical fluency in Python and practical experience using data science, ML and optimisation tooling
  • Experience delivering production‑quality systems with robust logging and testing
  • Confidence leading and guiding a full‑stack squad across modelling, software engineering and delivery discipline
  • Ability to communicate complex technical concepts clearly to a wide range of audiences
  • Pragmatic, outcome‑focused mindset with a strong bias for delivery and business impact
Your experience
  • Master’s degree or equivalent experience in data science, machine learning or operational research
  • Several years’ experience building or leading production machine learning or optimisation products at scale
  • Experience developing industrialised software, particularly data‑science‑led products
  • Experience in operational, transport, airline or network‑based domains is advantageous
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.


#J-18808-Ljbffr

Related Jobs

View all jobs

Lead Product Data Scientist - ML & Optimization for Airline

Lead Product Data Scientist

Lead Product Data Scientist - ML & Optimization for Airline

Senior Data Science Manager — Product & AI Leader

Senior Data Science Manager, Business Banking New Cardiff, London or Remote (UK)

Lead Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.