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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: Earn up to £100k with flexible remote work options.
- Why this job: Make an impact by working on innovative ML projects with cutting-edge tech.
- Qualifications: Experience in Python, LLM frameworks, and data pipelines is essential.
- Other info: Collaborate with a dynamic team and grow your career in data science.
The predicted salary is between 43200 - 72000 £ per year.
We are hiring a Data Scientist to help build and ship ML and LLM features in a regulated environment with sensitive data. You will 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 £100k
Working Environment: Fully Remote in UK
What you will 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 will 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 at mmatysik@trg-uk.com.
Data Scientist in Oxford employer: trg.recruitment
Contact Detail:
trg.recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in Oxford
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups or webinars, and connect with fellow data enthusiasts on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, ML models, or LLM frameworks. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨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 effectively 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 noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Scientist in Oxford
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! Tell us why you’re passionate about data science and how you can contribute to our mission. 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 tools mentioned in the job description, make sure to include them. We’re keen to see your hands-on experience and creativity!
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 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. Being able to discuss these technologies confidently will show that you're ready to hit the ground running.
✨Prepare Real-World Examples
Think of specific projects or experiences where you've successfully built and deployed models or created data pipelines. Be ready to explain your thought process, the challenges you faced, and how you overcame them. This will demonstrate your practical experience and problem-solving skills.
✨Communicate Clearly
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. Prepare to discuss how you would communicate your findings and insights effectively to different audiences. This skill is crucial in a collaborative environment.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the company’s approach to ML and LLM features, or 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.
