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- Tasks: Develop and deploy machine-learning models that make a real-world impact.
- Company: Join Kantar, a leading data and insights company shaping the future.
- Benefits: Enjoy flexible hybrid working, competitive salary, and generous leave policies.
- Other info: Collaborative team environment with opportunities for career growth.
- Why this job: Work on cutting-edge AI technology that simulates consumer behaviour at scale.
- Qualifications: Solid experience in data science and strong Python skills required.
The predicted salary is between 60000 - 80000 ÂŁ per year.
We go beyond the obvious, using intelligence, passion and creativity to inspire new thinking and shape the world we live in.
This role is about applying data science where it genuinely matters — in live, production environments that support large‑scale research operations around the world.
As a Senior Data Scientist on the Digital Twins team you’ll work on advanced modelling and analytics that improve the quality, reliability and performance of high‑volume data systems. You’ll partner closely with engineering, operational and commercial teams, taking ideas from hypothesis through to deployment, and ensuring models deliver real value once they’re live.
You’ll join a collaborative team of data scientists, analysts and engineers, working on complex, mission‑critical platforms that underpin the insights delivered to some of the world’s best‑known organisations.
Digital Twins at Kantar is an AI platform that simulates consumer behaviour at scale, enabling Kantar’s products to test scenarios and predict outcomes before they happen.
What you’ll be doing:
- Developing and deploying machine‑learning models in production environments
- Working end‑to‑end across the data science lifecycle: problem definition, modelling, deployment and monitoring
- Analysing new and existing data sources to improve decision‑making and model performance
- Designing feedback loops that continuously improve outcomes and data quality
- Collaborating closely with engineers to deliver scalable, reliable model predictions
- Communicating technical insights clearly to non‑technical stakeholders
The skills & experience you’ll need:
- Solid experience working as a data scientist on real‑world, production problems
- Strong Python skills (or a similar language used in applied data science)
- Experience with supervised learning and unsupervised techniques such as anomaly detection
- Exposure to cloud‑based model training, deployment and automation
- A strong sense of ownership and accountability for data science outputs
- Experience working with large consumer datasets or high‑traffic platforms is an advantage, but not essential.
Our tech environment:
You’ll work with modern data and analytics tooling across cloud platforms, including machine‑learning services, data pipelines and monitoring solutions. Our current ecosystem includes AWS technologies, with new development increasingly aligned to Azure.
What’s in it for you:
- Flexible hybrid working
- 25 days leave, 2 days paid for volunteering and life event leave
- Competitive salary and bonus (bonus dependent on role)
- Company pension
- Enhanced parental leave
- Healthcare options
- Wide range of flexible benefits
We are not able to offer visa sponsorship or assist with relocation support for this role. Please ensure you have the right to work in the country where this role is located before applying.
Location: Reading, King’s Road, United Kingdom
Kantar is the world’s leading data, insights and consulting company. We understand more about how people think, feel, shop, share, vote and view than anyone else. Combining our expertise in human understanding with advanced technologies, Kantar’s 30,000 people help the world’s leading organisations succeed and grow.
Senior Data Scientist - Digital Twins in London employer: Kantar
Contact Detail:
Kantar Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist - Digital Twins in London
✨Tip Number 1
Network like a pro! Reach out to current employees on LinkedIn or at industry events. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Show off your skills in real-time! Consider participating in hackathons or data science competitions. This not only sharpens your abilities but also gives you something impressive to talk about during interviews.
✨Tip Number 3
Prepare for those tricky interview questions! Brush up on your technical knowledge and be ready to discuss your past projects. We want to see how you think and solve problems, so practice explaining your thought process.
✨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 our team at Kantar.
We think you need these skills to ace Senior Data Scientist - Digital Twins in London
Some tips for your application 🫡
Show Your Passion: When writing your application, let your enthusiasm for data science shine through! We want to see how your passion aligns with our mission of using intelligence and creativity to inspire new thinking.
Tailor Your Experience: Make sure to highlight your relevant experience in data science, especially any work with machine learning models or large datasets. We love seeing how your skills can contribute to our Digital Twins team!
Be Clear and Concise: Communicate your technical insights in a way that's easy to understand. Remember, we value collaboration with non-technical stakeholders, so clarity is key in your written application.
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’re considered for this exciting opportunity with Kantar!
How to prepare for a job interview at Kantar
✨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning models and their deployment. Be ready to discuss your experience with Python and any cloud-based tools you've used, as these are crucial for the role.
✨Showcase Real-World Applications
Prepare examples of how you've tackled real-world problems using data science. Highlight specific projects where your models made a tangible impact, especially in production environments. This will demonstrate your ability to deliver value in a live setting.
✨Communicate Clearly
Since you'll be working with non-technical stakeholders, practice explaining complex concepts in simple terms. Think about how you can convey technical insights without jargon, making it relatable to those outside the data science field.
✨Collaborate and Engage
Emphasise your teamwork skills during the interview. Discuss how you've collaborated with engineers and other teams to enhance model performance and decision-making. Showing that you can work well in a collaborative environment is key for this role.