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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, fully remote work, and opportunities for professional growth.
- Other info: Collaborate with both technical and non-technical teams to drive innovation.
- Why this job: Make an impact by working with cutting-edge ML technologies in a dynamic environment.
- Qualifications: Experience in Python, LLM frameworks, and data pipeline development.
The predicted salary is between 36000 - 60000 £ per year.
Data Scientist | Fully Remote | Health and Wellbeing
We’re hiring an Data Scientist to help build and ship ML and LLM features in a regulated environment with sensitive data. You’ll work with engineering to move models from idea to production.
Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes.
Salary: Up to £55,000 – £65,000
Working Environment: Fully Remote in UK
What you’ll do
- Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing)
- Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost
- Create data pipelines for batch and streaming with Spark and Kafka
- Use Databricks and MLflow for experiments, deployment, and monitoring
What you’ll bring
- Hands-on Python for data science and ML
- Practical experience with LLM frameworks (e.g. LangChain)
- Familiar with Spark/Kafka and End-to-end pipeline experience
- Databricks, MLflow, Docker, Kubernetes
- Clear communication with technical and non-technical stakeholders
If you are interested apply below or email me directly mmatysik@trg-uk.com
Associate Data Scientist employer: trg.recruitment
Contact Detail:
trg.recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Associate Data Scientist
✨Tip Number 1
Network like a pro! Reach out to folks in the data science community on LinkedIn or join relevant groups. 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 projects, especially those involving Python, ML frameworks, and data pipelines. This will give 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, as you'll need to communicate with both technical and 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 seeing candidates who are proactive about their job search.
We think you need these skills to ace Associate 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 achievements!
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 team. Keep it concise but engaging – we love a good story!
Showcase Your Projects: If you've worked on any cool projects using scikit-learn, PyTorch, or any of the other tools mentioned, make sure to include them. We’re keen to see your hands-on experience and creativity in action!
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 from us!
How to prepare for a job interview at trg.recruitment
✨Know Your Tech Stack
Familiarise yourself with the tools mentioned in the job description, like Python, scikit-learn, and TensorFlow. Be ready to discuss your hands-on experience with these technologies and how you've used them in past projects.
✨Showcase Your LLM Knowledge
Since the role involves working with LLM frameworks like LangChain, prepare to talk about any relevant projects or research you've done. Highlight specific use cases you've worked on, such as Q&A or document processing.
✨Communicate Clearly
You'll need to explain complex concepts to both technical and non-technical stakeholders. Practice articulating your thoughts clearly and concisely, perhaps by explaining a project to a friend who isn't in tech.
✨Prepare for Scenario Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think of examples where you've built or tuned models, created data pipelines, or deployed ML features, and be ready to walk through your thought process.