Data Scientist

Data Science & Analytics (DSA) is central to how Trainline builds products, delights customers and grows the business. Data Scientists are embedded alongside Data Analysts in cross-functional teams across product and marketing, have a high degree of autonomy, and are empowered to drive the success of their teams using all data and techniques at their disposal. As a Data Scientist in the New Business team, you will help shape how Trainline grows beyond train tickets, using customer insights, experimentation and analytical techniques to uncover new opportunities, influence product strategy and create meaningful value. The role is hybrid, requiring Trainliners to work from the office a minimum of 60% of their time over a 12-week period. Tech stack: SQL, Python, R, Tableau, AWS Athena.

Responsibilities

Own data science work from start to finish within an embedded product team, from shaping the right question to delivering a solution and measuring its impact; Explore customer behaviour and product usage to uncover areas of friction, spot new opportunities and estimate the benefit of acting on them; Contribute to simple, seamless customer journeys by identifying where to remove barriers and add value; Design, run and analyse experiments using sound statistical methods, and help define metrics; Build, test and improve models such as forecasting, personalisation or customer behaviour prediction; Turn findings into clear, practical recommendations that help shape product and monetisation strategy, tailoring the message for both technical and non-technical audiences; Work in the New Business team to help Trainline grow beyond train tickets, including insurance, hotels, car hire, attractions and other travel experiences

Requirements

Hands-on experience applying data science to real product or customer problems, ideally within an embedded or cross-functional team; Confidence using Python and SQL to explore large datasets of customer activity, build models and write efficient, readable code; Experience of product engagement evaluation and measurement of success, for example running A/B tests or using front-end data to quantify the effectiveness of new features; The ability to explain complex ideas simply and adapt how you communicate for different audiences

Nice to have

Ideally, an interest in monetisation, advertising, recommendations or e-commerce; Familiarity with tools such as dbt, Looker or Tableau, although none of these are essential

Benefits

Private healthcare and dental insurance; Generous work from abroad policy (28-day Work from Abroad policy); 2-for-1 share purchase plans; EV Scheme; Extra festive time off; Family-friendly benefits; Clear career paths; Transparent pay bands; Personal learning budgets; Regular learning days