Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Create predictive models and analytics tools using Python and R.
- Company: Global market research firm with a focus on innovation.
- Benefits: 25 days annual leave, hybrid work model, and inclusive culture.
- Why this job: Join a dynamic team and make an impact with your data skills.
- Qualifications: Technical degree, coding skills, and experience in statistical analysis.
- Other info: Collaborative environment with opportunities for growth and learning.
The predicted salary is between 45000 - 55000 £ per year.
A global market research firm in Greater London seeks a talented Data Scientist to join the NextGen BHT team. You will develop predictive models and analytics tools using Python and R, collaborate with data scientists, and communicate insights to stakeholders.
The role requires a technical degree, coding proficiency, and experience in statistical analysis.
Enjoy benefits like 25 days annual leave and a hybrid work model where you can work on-site or remotely for part of the week. We are committed to fostering an inclusive workplace.
Hybrid Data Scientist — Python for Brand Analytics employer: Ipsos in the UK
Contact Detail:
Ipsos in the UK Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid Data Scientist — Python for Brand Analytics
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the company on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your predictive models and analytics tools. This is your chance to demonstrate your coding prowess in Python and R.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on statistical analysis concepts and coding challenges. We want you to feel confident when it’s showtime!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Hybrid Data Scientist — Python for Brand Analytics
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and R, as well as any relevant statistical analysis skills. We want to see how your background aligns with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Scientist position and how you can contribute to our NextGen BHT team. Keep it engaging and personal – we love to see your personality!
Showcase Your Projects: If you've worked on any predictive models or analytics tools, make sure to mention them in your application. We’re keen to see real examples of your work, so include links or descriptions that demonstrate your coding prowess and analytical skills.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us. Plus, it’s super easy!
How to prepare for a job interview at Ipsos in the UK
✨Know Your Python and R Inside Out
Make sure you brush up on your coding skills in Python and R. Be prepared to discuss specific projects where you've used these languages, and think about how you can demonstrate your proficiency through practical examples or even a coding challenge.
✨Understand Predictive Modelling
Familiarise yourself with different predictive modelling techniques and be ready to explain how you've applied them in past roles. It’s a good idea to have a couple of case studies in mind that showcase your analytical skills and the impact of your work.
✨Communicate Insights Clearly
Since you'll need to communicate findings to stakeholders, practice explaining complex data insights in simple terms. Think about how you can present your previous work in a way that highlights your ability to make data accessible and actionable for non-technical audiences.
✨Show Your Collaborative Spirit
This role involves working closely with other data scientists, so be ready to discuss your teamwork experiences. Share examples of how you've collaborated on projects, resolved conflicts, or contributed to a team’s success, as this will show you're a great fit for their inclusive workplace culture.