Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Use data to enhance loyalty programmes and create visual insights.
- Company: Expedia Group, a leader in travel technology with a collaborative culture.
- Benefits: Extensive benefits package, including health perks and professional development.
- Other info: Join a dynamic team in Greater London with great career growth potential.
- Why this job: Make a real impact on customer loyalty through data-driven decisions.
- Qualifications: Degree in a quantitative field and skills in SQL, Python, or R.
The predicted salary is between 35000 - 45000 £ per year.
Expedia Group is seeking a Data Scientist I in Greater London to utilize data for enhancing loyalty programs and CRM marketing. The role involves applying analytics to solve business problems, analyzing complex datasets, and creating visual insights and dashboards.
Ideal candidates should have a degree in a quantitative field and be proficient in SQL, Python, or R.
The position offers an extensive benefits package and encourages a collaborative work culture.
Data Scientist I, Loyalty Analytics employer: Expedia Group
Contact Detail:
Expedia Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist I, Loyalty Analytics
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Expedia Group. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those involving SQL, Python, or R. This will help you stand out and demonstrate your capabilities beyond just a CV.
✨Tip Number 3
Prepare for the interview by brushing up on common data science problems and analytics techniques. Practising how to explain your thought process can really impress the hiring team.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist I, Loyalty Analytics
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with SQL, Python, or R in your application. We want to see how you've used these tools to tackle real-world problems, especially in loyalty analytics or CRM marketing.
Tell Your Story: Use your cover letter to share your journey in the data world. We love hearing about your passion for data and how it drives you to solve business challenges. Make it personal and engaging!
Be Clear and Concise: When filling out your application, keep your language straightforward and to the point. We appreciate clarity, so avoid jargon unless it's necessary. Remember, we want to understand your thought process easily!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Expedia Group
✨Know Your Data Tools
Make sure you brush up on your SQL, Python, and R skills before the interview. Be ready to discuss how you've used these tools in past projects, as well as any specific techniques or libraries that are relevant to loyalty analytics.
✨Showcase Your Analytical Mindset
Prepare to talk about how you've approached solving complex business problems with data. Think of examples where your analysis led to actionable insights, especially in CRM marketing or loyalty programmes, and be ready to explain your thought process.
✨Visual Insights Matter
Since the role involves creating visual insights and dashboards, consider bringing a portfolio of your previous work. If you have examples of dashboards or visualisations that effectively communicated data stories, be sure to highlight them during the interview.
✨Emphasise Collaboration
Expedia Group values a collaborative work culture, so be prepared to discuss how you've worked in teams. Share experiences where you collaborated with others to achieve a common goal, particularly in data-driven projects, to show you're a team player.