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About the Role
As a Data Scientist in our New Business team, you'll help shape how Trainline grows beyond train tickets by exploring new ways to add value throughout the customer journey. You'll use customer insights, experimentation, and analytical techniques to uncover new opportunities, influence product strategy, and create meaningful value for both our customers and Trainline.
Responsibilities
- Own data science work from start to finish within an embedded product team, from shaping the right question with your colleagues 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 we can 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 that enhance the customer experience and support business growth
- Turn your findings into clear, practical recommendations that help shape product and monetisation strategy, tailoring your message for both technical and non-technical audiences
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 to evaluate product effectiveness or using front-end data to quantify the effectiveness of new features and how it changes user engagement.
- The ability to explain complex ideas simply and adapt how you communicate for different audiences
- Ideally, an interest in monetisation, advertising, recommendations or e-commerce, and familiarity with tools such as dbt, Looker or Tableau, although none of these are essential
Skills
- Python
- SQL
- R
- Tableau
- AWS Athena
- dbt
- Looker
- Data Science
- Data Analytics
- Experimentation
- Statistical Methods
- Forecasting
- Personalisation
- Customer Behaviour Prediction
Location
- London
- Paris
- Barcelona
- Milan
- Edinburgh
- Madrid
Work Type
- Hybrid
- Work from Abroad Policy
Experience Level
- Data Scientist
Benefits
- Private healthcare & dental insurance
- Generous work from abroad policy
- 2-for-1 share purchase plans
- EV Scheme
- Extra festive time off
- Excellent family-friendly benefits
- Personal learning budgets
- Regular learning days
About the Company
- Trainline's purpose is to empower greener travel choices, connecting people and places.
- Trainline enables millions of travellers to find and book the best value tickets across carriers, fares, and journey options through our highly rated mobile app, website, and B2B partner channels.
- We’re Europe’s leading independent rail platform, helping millions of travellers find and book the best-value rail and coach journeys across our app, website and partner channels.
- Our job is to make the green travel choice the best choice. By building a better train travel experience, we help more people choose rail - creating a positive impact for customers, our business and the planet.
- We’re a team of more than 1,000 Trainliners from over 50 nationalities, working across London, Paris, Barcelona, Milan, Edinburgh and Madrid.
- Data Science & Analytics (DSA) is central to how we build products, delight our customers and grow our business.
- Our Data Scientists are embedded alongside Data Analysts in cross-functional teams which exist across product and marketing.
- Data Scientists have a high degree of autonomy and are empowered to drive the success of their teams, using all data and techniques at their disposal.
- Data Science and Analytics at Trainline exists within the wider data organisation as part of the tech org, and is complemented by data engineering teams, data platform teams, and ML teams for when deep ML and AI techniques are required.
- Our autonomous model creates a huge opportunity for personal influence and impact – as the data scientist on the team you will be actively driving innovation on the team by contributing to strategy, execution and continuous learning.
- We know that having a diverse team makes us better and helps us succeed. And we mean all forms of diversity - gender, ethnicity, sexuality, disability, nationality and diversity of thought. That's why we're committed to creating inclusive places to work, where everyone belongs and differences are valued and celebrated.