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We go beyond. For everyone. Our vision is to be the most loved, progressive and responsible way to travel for generations to come. Now we're looking for the people who can deliver this, every day.
Since we took over on the East Coast mainline, we've been changing the face of rail travel. Our new Azuma train has brought faster journey times, more space and greater reliability. Our exciting plans to embrace new ideas, experiences, backgrounds and ambitions make this the ideal time to join.
Bringing passion. Being bold. Always caring. Owning it. They're the values that make us LNER.
Are you on board?
Are you fascinated by the power of data and the possibilities of machine learning? At LNER, we're on a mission to revolutionise rail travel and data is at the heart of it. As a Data Scientist Intern on our innovative Machine Learning Team, you won't just be learning - you'll be helping to shape the future of transport.
In this role, you'll dive into a wealth of rich, real-world data, performing exploratory analysis and building statistical models that turn bold ideas into practical, tested proof-of-concepts. From spotting trends in passenger behaviour to solving operational challenges, your insights will help unlock smarter, faster, and more personalised experiences for millions of travellers.
Working alongside a team of expert data scientists and ML product managers contributing to exciting projects from day one, exploring feasibility, building models, and helping bring cutting-edge ideas to life. You'll also get hands-on with best practices in coding, testing, and deploying ethical AI solutions.
If you're curious, collaborative, and ready to turn data into action - jump on board and be part of something transformative.
Within this role, you'll also be involved in
Proof of concepts
- Performing detailed exploratory analysis on new data sources to gain a detailed understanding of the underlying trends and its potential use in solving the business problem.
- Utilising the AWS machine learning stack, developing statistical algorithms and machine learning models to run fast paced proof of concepts from within the portfolio to identify areas of value generation.
- Working with Senior Data Scientists to evaluate model performance to select the best model that solves the problem provided by the product team.
- As required, working with members of the team to undertake data engineering tasks such as data manipulation, visualisation and feature development.
- Working with senior members of the team on improving code quality to ensure all code is easy to read, performs the objective required and commented thoroughly so that it can be understood easily by others in the team.
- Contributing to business wide engagement; confidently sharing project outputs with a wide range of stakeholders, in an easily digestible format, to maintain trust and transparency of machine learning within the business.
- Ensuring codebase is left in a suitable condition that it can be picked up by other members of the team should the POC be productionised.
Governance and ways of working
- Supporting the Machine Learning team by always working within governing principles to enable the team to maintain best practice guidance (e.g. Code of Practice, Ethics).
- Contributing to business cases that address productionised solutions of POCs.
Learning and development
- Continuously demonstrating and developing subject matter expertise in data science theory and practice.
- Continuously staying up to date with developments in machine learning technology, approaches, coding and model development.
- Maintaining a secondary competence role for the purpose of contingency planning.
- Ensuring relevant training and competencies are gained and maintained in order to resource our continued service during times of disruption.
What you'll need
Key competencies
- Data-driven mindset – Able to explore, analyse, and visualise data to tell compelling stories to both technical and non-technical audiences.
- Strong analytical skills – Confident in data manipulation and statistical model development, using a variety of tools (including open-source) and best coding practices.
- Curious problem solver – Takes an experimental and creative approach to tackling complex challenges and assessing solution feasibility.
- Collaborative team player – Works effectively with data scientists, ML engineers, and product managers to drive project success.
- Customer-focused – Understands user needs and translates them into data science opportunities.
- Motivated learner – Continuously seeks to grow technical and communication skills, embraces feedback, and shares knowledge across the team.
- Performance-driven – Strives for high-quality, efficient delivery and takes ownership of personal and team success.
Technical essentials
- Proficient knowledge of machine learning fundamentals, including key concepts such as supervised and unsupervised learning, model evaluation, and feature engineering.
- Experienced in writing well-structured Python code for machine learning algorithms.
- Knowledge of basic machine learning libraries such as NumPy, Pandas, Polars, Scikit-learn, PyTorch, Tensorflow, etc.
- Experienced in at least one Python data visualisation libraries such as Matplotlib, Seaborn or Plotly.
- A solid grasp of standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference.
- Experience in working with large amounts of raw data; preparing, cleansing and processing.
- An understanding of coding best practices and experience with code and data versioning (using Git/CodeCommit), code quality and optimisation, error handling, logging, monitoring, validation and alerting.
- Is not afraid to experiment; has a ‘test and learn' approach mentality.
Desirables
- Experience in working with AWS Machine Learning Stack i.e. Sagemaker Studio, Athena.
- Familiarity with Tableau and/or other visualisation tools (e.g. Power BI).
- Experience or familiarity with writing basic unit or integration tests for code to ensure functionality and reliability.
- Experienced in stakeholder management and communication, in particular explaining data analyses to audiences.
- Interest or knowledge of the rail industry.
What you'll get
- Free travel on LNER + 75% off other companies' tickets (for you & dependents)
- Discounted international train tickets (after one year's service)
- 50% discount on LNER tickets for friends & family
- Generous pension scheme
- Annual cycle to work schemes
- Discount, savings and cashback scheme from top retailers
- Health & wellbeing schemes and discounts
- Host of training opportunities to help further your career
- Rewards & awards to recognise when you shine
What we believe
To be the most loved, progressive and responsible train operating company, we must make a meaningful difference – always doing what's right for our customers, our people, the communities and destinations we serve, the future of the industry we lead and the environment we cherish.
We know that our people are the beating heart of everything we do. We are committed to creating an inclusive, engaged culture that supports everyone at every stage of their journey – and ensures that when you're at LNER, you can always be you. No wonder most people never want to leave!
