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- Tasks: Shape products and solve real problems using your data science expertise.
- Company: Fast-growing tech company focused on advanced technology and complex systems.
- Benefits: Up to £85,000 salary, fully remote work, and fantastic benefits.
- Why this job: Make a real impact with your models in a supportive, innovative environment.
- Qualifications: Strong Python or R skills, experience with ML frameworks, and a quantitative degree.
- Other info: Join a dynamic team where your contributions are valued and career growth is encouraged.
The predicted salary is between 51000 - 85000 £ per year.
Want your models to ship, your ideas to shape products, and your work to solve real, high impact problems? If you’re craving a role where your data science expertise genuinely changes how products are built and decisions are made… this is it.
We’re partnered with a fast‑growing technology company that applies cutting edge data science to large scale, highly complex real world environments. This isn’t a role where your work gathers dust in a slide deck, this is hands on, production focused data science at the heart of the organisation’s core technology.
You’ll join a small, experienced team where your contributions have direct, visible impact. Expect autonomy, influence, and the chance to push your technical boundaries daily.
What You’ll Be DoingYou’ll work across the full data science lifecycle; shaping problems, exploring data, experimenting with models, and deploying real solutions that drive real outcomes.
- Building and deploying machine learning models used directly in live products (e.g., anomaly detection, forecasting, clustering, recommendation)
- Working hands-on with large, messy, real-world datasets and time series data
- Designing and maintaining clean, scalable Python data pipelines
- Applying statistical thinking, rigorous experimentation, and optimisation
- Collaborating seamlessly with engineering and product to take ideas end‑to‑end
- Communicating insights clearly and transparently, no black‑box science
If you love seeing your models in production and solving problems with measurable results, you’ll thrive here.
What We’re Looking ForYou don’t need to tick every box, but you should recognise yourself in most of these:
- Strong skills in Python or R
- Experience with ML frameworks such as Scikit‑learn, TensorFlow, PyTorch
- A solid understanding of machine learning, statistics, and modelling best practice
- Competence with SQL and real‑world, imperfect data
- Experience or interest in time series analysis and forecasting
- Familiarity with modern dev practices: Git, Docker, CI/CD, data pipelines
- A mindset built around ownership, robustness, and production‑quality output
Master’s or PhD in a quantitative field such as: Data Science, Physics, Mathematics, Engineering, Computer Science, or similar.
Why Join?If you want a role where you’re trusted, challenged, and supported, this delivers:
- Competitive salary up to £85,000 + great benefits
- Fully remote working anywhere in the UK
- Work on genuinely complex, meaningful problems with real-world impact
- Learn from and collaborate with a highly experienced Lead Data Scientist and top tier engineers
- A modern technology stack and engineering culture designed for quality, velocity, and clarity
- A growing company where your voice is heard and your work truly matters
- Autonomy, influence, and the chance to continually sharpen your craft
This is the perfect fit for someone who wants to move fast, think deeply, and build things that matter.
Interested? Apply now for a fantastic opportunity. Please note: Applicants must have full right to work in the UK. Sponsorship is not available.
Data Scientist in London employer: HireQ Talent
Contact Detail:
HireQ Talent 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 people in the industry, attend meetups, and connect on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data science projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Mock interviews with friends or mentors can help you articulate your thought process and technical skills clearly.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Data Scientist role. Highlight your Python or R expertise, ML frameworks you've worked with, and any hands-on experience with real-world datasets.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data science and how you can contribute to our team. Share specific examples of projects where your models made a real impact.
Showcase Your Projects: If you've got a portfolio of projects, don’t hesitate to share it! We love seeing practical applications of your skills, especially those involving machine learning models and data pipelines.
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at HireQ Talent
✨Know Your Data Science Stuff
Make sure you brush up on your Python or R skills, and be ready to discuss your experience with machine learning frameworks like Scikit-learn or TensorFlow. Prepare to explain how you've tackled real-world datasets and the statistical methods you've applied.
✨Showcase Your Problem-Solving Skills
Be prepared to share specific examples of how you've built and deployed models that had a tangible impact. Think about times when your work directly influenced product decisions or improved outcomes, and be ready to discuss these in detail.
✨Communicate Clearly
Since this role emphasises clear communication, practice explaining complex concepts in simple terms. You might be asked to present your insights from a project, so make sure you can articulate your thought process and findings without jargon.
✨Familiarise Yourself with Modern Practices
Get comfortable discussing modern development practices like Git, Docker, and CI/CD. Be ready to talk about how you've used these tools in your previous projects, as they are crucial for maintaining clean and scalable data pipelines.