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- Tasks: Research and deploy machine learning features in a fully remote role.
- Company: Join a forward-thinking company focused on health and wellbeing.
- Benefits: Competitive salary up to £100k and fully remote work in the UK.
- Why this job: Make an impact by working with cutting-edge ML technologies and sensitive data.
- Qualifications: Hands-on Python experience and familiarity with LLM frameworks required.
- Other info: Collaborate with both technical and non-technical teams in a dynamic environment.
The predicted salary is between 21600 - 36000 £ per year.
A UK-based health and wellbeing organisation is hiring a Data Scientist to build and deploy production ML and GenAI systems. The role is hands-on and end to end, covering data preparation, model development, and deployment across traditional ML and LLM-based use cases.
You will work on real production problems rather than research-only work, owning models from first iteration through to live deployment. You will collaborate closely with other data scientists, data engineers, and DevOps, with the freedom to shape how GenAI and ML are used across the platform.
Tech stack:
- Python
- PyTorch or TensorFlow
- scikit-learn
- Spark
- Kafka
- Databricks
- LangChain and RAG-based GenAI systems
- Cloud-native Azure environment
Important Details:
- Fully remote across the UK
- Up to £80,000 – £100,000 (DOE)
- 2-3 stage interview process
- No sponsorship available
Interested, or know someone who would be? Click apply or get in touch directly on mgojzewski@trg-uk.com
Data Scientist employer: trg.recruitment
Contact Detail:
trg.recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, ML, and LLM frameworks. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms – it’s key when communicating with non-technical stakeholders.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with Python, ML frameworks, and any relevant projects you've worked on. We want to see how your skills match what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our mission at StudySmarter. Keep it concise but impactful!
Showcase Your Projects: If you've got any cool projects or contributions to open-source that demonstrate your skills in ML or data pipelines, make sure to mention them. We love seeing practical applications of your knowledge!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at trg.recruitment
✨Know Your Tech Stack
Make sure you’re familiar with the tools mentioned in the job description, like Python, scikit-learn, and TensorFlow. Brush up on your knowledge of LLM frameworks and data pipelines using Spark and Kafka, as these will likely come up during the interview.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built or deployed ML models. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Communicate Clearly
Since the role involves liaising with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will show that you can bridge the gap between different teams and ensure everyone is on the same page.
✨Ask Insightful Questions
Prepare a few thoughtful questions about the company’s approach to health and wellbeing, or their use of ML and LLM features. This shows your genuine interest in the role and helps you assess if the company aligns with your values and career goals.
