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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: Experience in Python, LLM frameworks, and end-to-end data pipelines.
- 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 using Python, scikit-learn, or any of the tools mentioned in the job description. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and practical coding challenges. We recommend practicing with real-world problems to get comfortable with the tech stack.
✨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 seeing candidates who are proactive about their job search.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, ML frameworks, and any relevant projects. We want to see how your skills align with the role, so don’t be shy about showcasing your best work!
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 Relevant Projects: If you've worked on any projects involving LLMs or data pipelines, make sure to mention them! We love seeing practical examples of your work, especially if they relate to our tech stack.
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!
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. Highlight your hands-on experience with Databricks and MLflow, and be ready to explain how you tackled challenges in those projects.
✨Communicate Clearly
Since the role involves liaising with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will demonstrate your ability to bridge the gap between different teams.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s approach to health and wellbeing, and how they handle sensitive data. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
