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- Tasks: Drive growth by analysing data and building predictive models for an online marketplace.
- Company: Leading online marketplace focused on enhancing customer experience.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Make a real impact on e-commerce while working with data in a dynamic environment.
- Qualifications: Over 2 years of data science experience, proficient in Python and SQL.
- Other info: Collaborative team culture with exciting projects in Bournemouth or Manchester.
The predicted salary is between 40000 - 50000 £ per year.
A leading online marketplace is seeking a Data Scientist to drive growth and enhance customer experience. The role involves collaborating with cross-functional teams to analyze data, build predictive models, and influence commercial decisions.
The ideal candidate will have:
- Over 2 years of experience in data science
- Strong proficiency in Python and SQL
- The ability to communicate insights effectively
This position offers a competitive salary and a hybrid work model based in Bournemouth or Manchester.
Growth Data Scientist - E-commerce (Hybrid) in Bournemouth employer: OnBuy
Contact Detail:
OnBuy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Growth Data Scientist - E-commerce (Hybrid) in Bournemouth
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those working in e-commerce or data science. A friendly chat can lead to valuable insights and even job referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data projects, especially those involving predictive models. This will give potential employers a taste of what you can do and how you can drive growth.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. Be ready to discuss how you've used these tools to influence commercial decisions in past roles. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace Growth Data Scientist - E-commerce (Hybrid) in Bournemouth
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data science, especially with Python and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about driving growth in e-commerce and how your background makes you the perfect fit for our team. Keep it engaging and personal!
Showcase Your Communication Skills: Since the role involves influencing commercial decisions, we need to see that you can communicate insights effectively. Include examples in your application where you've successfully conveyed complex data findings to non-technical stakeholders.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates during the process!
How to prepare for a job interview at OnBuy
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially in Python and SQL. Be ready to discuss your past projects and how you've used these skills to drive growth or improve customer experience.
✨Show Off Your Analytical Skills
Prepare to showcase your ability to analyse data and build predictive models. Think of specific examples where your insights influenced commercial decisions, and be ready to explain your thought process.
✨Collaborate Like a Pro
Since the role involves working with cross-functional teams, be prepared to discuss how you've successfully collaborated with others in the past. Highlight any experiences where teamwork led to better outcomes.
✨Communicate Clearly
Effective communication is key! Practice explaining complex data insights in simple terms. You might even want to prepare a mini-presentation to demonstrate how you can convey your findings to non-technical stakeholders.