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For Companies At a Glance
- Tasks: Shape problems, explore data, and deploy impactful machine learning models.
- Company: Fast-growing tech company focused on real-world data science solutions.
- Benefits: Up to ÂŁ85,000 salary, great benefits, and fully remote work.
- Why this job: Make a real impact with your data science expertise in a supportive 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 visible.
The predicted salary is between 51000 - 85000 ÂŁ 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 fastâgrowing 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.
Youâll 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 Youâll Be Doing
Youâll 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 endâtoâend
- Communicating insights clearly and transparently, no blackâbox science
If you love seeing your models in production and solving problems with measurable results, youâll thrive here.
What Weâre Looking For
You donât 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 Scikitâlearn, TensorFlow, PyTorch
- A solid understanding of machine learning, statistics, and modelling best practice
- Competence with SQL and realâworld, 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 productionâquality output
Education
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 youâre trusted, challenged, and supported, this delivers:
- Competitive salary up to ÂŁ85,000 + 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.
Locations
Data Scientist in Devon, Plymouth employer: HireQ Talent
Contact Detail:
HireQ Talent Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Data Scientist in Devon, Plymouth
â¨Tip Number 1
Network like a pro! Reach out to people in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that arenât even advertised yet.
â¨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning models and data pipelines. This gives potential employers a taste of what you can do.
â¨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. We recommend simulating real interview scenarios with friends or mentors to boost your confidence.
â¨Tip Number 4
Donât forget to apply through our website! Itâs the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Data Scientist in Devon, Plymouth
Some tips for your application đŤĄ
Show Your Passion for Data Science: When writing your application, let your enthusiasm for data science shine through! Share specific examples of projects or models you've worked on that had a real impact. We love seeing candidates who are genuinely excited about using their skills to solve complex problems.
Tailor Your CV and Cover Letter: Make sure to customise your CV and cover letter for the Data Scientist role. Highlight relevant experience with Python, machine learning frameworks, and any hands-on work with messy datasets. We want to see how your background aligns with what we do at StudySmarter!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your skills and experiences, avoiding jargon where possible. We appreciate transparency and clarity, so make it easy for us to understand your qualifications.
Apply Through Our Website: Donât forget to submit your application through our website! Itâs the best way for us to receive your details and ensures youâre considered for the role. Plus, it shows youâre serious about joining our team at StudySmarter!
How to prepare for a job interview at HireQ Talent
â¨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially around machine learning and statistics. Be ready to discuss your experience with Python or R, and any frameworks like Scikit-learn or TensorFlow that you've used. Theyâll want to see how you can apply these skills in real-world scenarios.
â¨Showcase Your Problem-Solving Skills
Prepare to talk about specific projects where youâve tackled complex problems. Highlight how you shaped the problem, explored the data, and deployed solutions. Use examples that demonstrate your ability to work with messy datasets and time series data, as this is crucial for the role.
â¨Communicate Clearly
Since the role involves collaborating with engineering and product teams, practice explaining your insights in a clear and transparent manner. Avoid jargon and be prepared to break down your thought process so that even non-technical stakeholders can understand the impact of your work.
â¨Familiarise Yourself with Modern Practices
Get comfortable discussing modern development practices like Git, Docker, and CI/CD. Theyâll likely ask how you maintain clean, scalable data pipelines, so be ready to share your approach to ensuring production-quality output and robustness in your work.