At a Glance
- Tasks: Drive insights and strategy for product growth using data science techniques.
- Company: Join Trainline, Europe's number 1 rail app, focused on sustainable travel.
- Benefits: Enjoy private healthcare, generous leave, and a clear career growth path.
- Other info: Hybrid work model with opportunities for personal influence and development.
- Why this job: Make a real impact in a fast-paced environment with innovative projects.
- Qualifications: 2+ years in data science, strong analytical and communication skills required.
The predicted salary is between 28800 - 48000 £ per year.
About us
We are champions of rail, inspired to build a greener, more sustainable future of travel. 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.
Great journeys start with Trainline. Now Europe's number 1 downloaded rail app, with over 125 million monthly visits and £5.9 billion in annual ticket sales, we collaborate with 270+ rail and coach companies in over 40 countries. We want to create a world where travel is as simple, seamless, eco-friendly and affordable as it should be.
Today, we're a FTSE 250 company driven by our incredible team of over 1,000 Trainliners from 50+ nationalities, based across London, Paris, Barcelona, Milan, Edinburgh and Madrid. With our focus on growth in the UK and Europe, now is the perfect time to join us on this high-speed journey.
Introducing Data Science & Analytics at Trainline
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.
As a Data Scientist, you will be involved in driving insights and strategy for the product team, creating and measuring value through experimentation, creating focus through metrics and goals, and building deep learning about what is most impactful for each team. You will be able to determine the underlying dynamics of our complex ecosystem and use this to deliver insights and strategic direction, but your main focus will be a complete obsession with driving impact within the product team, drawing on whatever analytical and statistical techniques that will unlock the most benefits.
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.
As a Data Scientist in our Marketing DSA team, you'll be working in a fast-paced and agile environment, working with large marketing budgets to drive growth at Trainline. Furthering our understanding of return on investment in a privacy first world whilst understanding how we perform in a complex and competitive marketing landscape presents many opportunities to develop and hone new methodology whilst having a big impact on the business.
As a Data Scientist, you will be responsible for influencing product and business outcomes, have the autonomy to make things happen and must obsess about having business impact. More specifically you will:
- Develop deep understanding of our product experiences and opportunities for growth.
- Actively contribute to roadmap and goals for the product team.
- Drive regular cross functional team reviews to measure progress toward goals.
- Discover and articulate new product opportunities helping shape the team's direction.
- Support product experiments, launches, growth through data-driven decision making while keeping the team accountable and impactful.
- Define focus through metrics to enable a broad spectrum of learning from experimentation/release cycles.
We'd love to hear from you if you have:
- 2+ years commercial experience using data science and analytics to drive business decisions.
- Ability to distil and communicate results of complex analysis clearly and effectively to all levels including senior management.
- 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.
- Ability to navigate data sets of varying complexity/ambiguity and conduct analysis to derive clear insights and actionable results.
- Strong PowerPoint and presentation/communication skills.
- Strong data visualisation skills using tools like Tableau, Spotfire, Power BI etc.
- Expertise in predictive modelling, including both parametric (e.g. logit/probit) and non-parametric (e.g. random forest, neural net) techniques as well as wider ML techniques like clustering / random forest (desirable).
Tech Stack: SQL, Python, R, Tableau, AWS Athena + More!
More information
Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad policy, 2-for-1 share purchase plans, an EV Scheme to further reduce carbon emissions, extra festive time off, and excellent family-friendly benefits.
We prioritise career growth with clear career paths, transparent pay bands, personal learning budgets, and regular learning days. Jump on board and supercharge your career from day one!
We operate a hybrid model to work and ask that Trainliners work from the office a minimum of 60% of their time over a 12-week period. We also have a 28-day Work from Abroad policy.
Our values:
Think Big - We're building the future of rail
Own It - We focus on every customer, partner and journey
Travel Together - We're one team
Do Good - We make a positive impact
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.
Interested in finding out more about what it's like to work at Trainline? Why not check us out on LinkedIn, Instagram and Glassdoor!
Data Scientist in London employer: Trainline
Trainline is an exceptional employer that fosters a dynamic work culture where innovation and collaboration thrive. With a strong focus on employee growth, the company offers numerous opportunities for professional development and engagement in meaningful projects that drive organisational transformation. Located in a vibrant environment, Trainline supports a healthy work-life balance and encourages its employees to embrace new ways of working, making it an attractive place for those seeking rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Trainline.
✨Apply Directly through Our Website
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We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Trainline, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Trainline. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Trainline
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Trainline!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
