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- Tasks: Develop predictive models and analytical products to drive business decisions.
- Company: Join Legend, a leading company in iGaming and personal finance.
- Benefits: Flexible work-life balance, annual bonuses, and exciting global events.
- Why this job: Make a real impact with data science in a supportive, high-performing team.
- Qualifications: Master's degree in a quantitative field and experience in data science techniques.
- Other info: Diverse perspectives are valued; apply even if you don't meet every qualification.
The predicted salary is between 36000 - 60000 £ per year.
About Legend
We’re Legend. The team quietly building #1 products that make noise in the most competitive comparison markets in the world. iGaming. Sports Betting. Personal Finance. We exist to build better experiences. From amplified career paths to supercharged online journeys — for our people and our users, we deliver magic rooted in method. With over 550 Legends and counting, we’re helping companies turbocharge their brand growth in over 22 countries worldwide.
If you’re looking for a company with momentum and the opportunity to progress at pace, Legend has it. Unlock the Legend in you.
The Role
Legend is hiring a Data Scientist to join our central Data & Analytics function, working alongside data analysts, engineers, and senior data scientists. The role contributes to the development of predictive models and analytical products that drive decision-making across marketing, product, and commercial teams. This position is ideal for someone ready to apply numerical modelling and engineering skills to real-world business problems, working within a supportive, high-performing environment where ownership, rigour, and learning are prioritised. Projects span various data science domains, including anomaly detection, forecasting, optimisation, recommendations, ranking, experimentation, and AI, each focused on measurable business outcomes and delivered through collaboration with data and product teams.
In this role, we value diverse perspectives and encourage you to apply even if you don’t meet every qualification listed.
Your Impact:
- Scope and validate analytical solutions aligned with clear business objectives
- Prepare and clean data in collaboration with engineers and analysts to ensure accuracy and usability
- Build models (under mentorship) using the full range of data science techniques, from statistics and econometrics to machine learning and mathematical optimisation.
- Contribute to model development across supervised and unsupervised ML techniques under mentorship
- Monitor and document model performance, flagging issues and iterating where appropriate
- Present findings clearly to technical and non-technical audiences to inform decision-making across teams
What You’ll Bring:
- Master’s degree in a quantitative field (e.g. Mathematics, Physics, Engineering, Computer Science, Economics)
- Self-motivated with a researcher’s mindset to tackle ambiguous challenges and drive solutions with minimal guidance
- Demonstrated experience applying data science techniques to business problems
- Proficient in SQL, Python, and standard data science libraries
- Foundational engineering skills, including version control (Git), collaborative development tools (Github) and command-line tools (Bash)
- Self-directed learner who thrives in cross-functional teams
Nice to haves:
- A PhD or demonstrated research experience
- Exposure to cloud-based data environments (Snowflake, AWS, Airflow or similar)
- Experience working on model deployment and Docker containers
- Knowledge of A/B testing frameworks
The Interview Process:
- 1st: Initial Chat with Talent Partner (30 mins via Zoom)
- 2nd: Interview with the hiring manager (1 hour video via Zoom)
- 3rd: Technical Task with the hiring team (1 hour video via Zoom)
- 4th: Final interview with our team (1 hour video via Zoom)
Why Legend?
- Super smart colleagues to work alongside and learn from.
- Engaging development opportunities at all levels.
- Tailored flexibility for your work-life balance.
- Annual discretionary bonus to reward your efforts.
- Paid annual leave PLUS a well-deserved break to recharge your batteries during the festive season. Our offices are closed between Christmas and New Year’s, allowing you to enjoy downtime without dipping into your annual allowance.
- Long term incentive plan so we can all share in the growth and success of Legend.
- Exciting global Legend events, where we unite in person to ignite our shared passion and unveil the exciting strategies for the year ahead.
- Unlock your full potential by joining the Legend team. To support you on this journey, we provide an extensive array of benefits and perks, as outlined in our global offerings above. For country specific benefits please reach out to your talent partner.
Legend is an Equal Opportunity Employer, but that’s just the start. We believe different perspectives help us grow and achieve more. That’s why we’re dedicated to hiring and developing the most talented and diverse team- which includes individuals with different backgrounds, abilities, identities and experiences. If you require any reasonable adjustments throughout your application process, please speak to your Talent Partner or contact the team on [email protected], and we’ll do all we can to support you.
Data Scientist in London employer: Legend
Contact Detail:
Legend Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Legend on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for those interviews! Brush up on your data science skills and be ready to discuss how you've tackled real-world problems. Practice explaining your thought process clearly, as you'll need to impress both technical and non-technical folks.
✨Tip Number 3
Show off your projects! If you've worked on any cool data science projects, make sure to highlight them during your interviews. Bring examples that demonstrate your skills in SQL, Python, and machine learning techniques.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Legend team.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight how your skills and experiences align with the Data Scientist role. We want to see how you can contribute to our mission at Legend!
Showcase Your Skills: Don’t just list your qualifications; demonstrate them! Include specific examples of how you've applied data science techniques to solve real-world problems. This will help us see your potential impact.
Be Authentic: We value diverse perspectives, so don’t hesitate to share your unique journey and experiences. Let us know what makes you tick and how you approach challenges in your work.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It’s the easiest way for us to keep track of your application and ensure it reaches the right people!
How to prepare for a job interview at Legend
✨Know Your Data Science Stuff
Make sure you brush up on your data science techniques, especially those mentioned in the job description like predictive modelling and machine learning. Be ready to discuss how you've applied these skills to real-world business problems, as this will show your practical experience.
✨Prepare for Technical Questions
Since you'll be working with SQL and Python, expect some technical questions or tasks during the interview. Practice coding challenges and be familiar with data manipulation libraries. This will help you feel more confident when tackling the technical task with the hiring team.
✨Showcase Your Collaboration Skills
Legend values teamwork, so be prepared to discuss your experiences working in cross-functional teams. Share examples of how you've collaborated with engineers and analysts to solve complex problems, as this will highlight your ability to thrive in a supportive environment.
✨Communicate Clearly
You'll need to present findings to both technical and non-technical audiences, so practice explaining complex concepts in simple terms. Think about how you can convey your insights effectively, as strong communication skills are key to influencing decision-making across teams.
