At a Glance
- Tasks: Design and build AI systems for scientific discovery and decision support.
- Company: Join a global team focused on innovative educational products.
- Benefits: Enjoy flexible working hours and a collaborative environment.
- Other info: Opportunity to work with frontier LLMs and develop production-ready solutions.
- Why this job: Make a real impact using cutting-edge machine learning and AI technologies.
- Qualifications: Experience in data science, machine learning, and strong Python skills required.
The predicted salary is between 60000 - 80000 £ per year.
Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? Would you enjoy turning complex scientific and business challenges into practical, production‑ready AI solutions that create real user value? Our global team supports products that educate students to digital charting and prepare them to document care in today's modern clinical environment. We maintain a stable product and value trust, respect, collaboration, agility, and quality.
Responsibilities
- Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.
- Work with large‑scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.
- Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.
- Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence‑grounded generation.
- Build, evaluate, fine‑tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.
- Write clean, tested, production‑quality Python and contribute reusable data‑science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.
- Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data‑science systems.
- Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behaviour, insights, trade‑offs, and recommendations clearly to technical and non‑technical audiences.
Qualifications
- Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area.
- Experience working with frontier LLMs such as OpenAI's GPTs, Anthropic's Claude, and Google's Gemini, including fine‑tuning LLMs and/or SLMs.
- Strong Python skills and a habit of writing clean, maintainable, well‑tested code.
- A solid grasp of machine‑learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement.
- Experience working with structured, semi‑structured, or unstructured data, especially large‑scale text or content datasets.
- Familiarity with common data science and machine‑learning tools such as Pandas, NumPy, SciPy, Scikit‑learn, PyTorch, TensorFlow, or Matplotlib.
- The ability to translate complex and ambiguous requirements into practical, measurable, data‑driven solutions, with strong analytical thinking, problem‑solving skills, and attention to quality.
- Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production‑ready systems that deliver real user value.
Benefits
Working Pattern – flexible hours – flexing the times when you work in the day to help you fit everything in and work when you are most productive.
Data Scientist II in Oxford employer: RELX Group
Join a forward-thinking company that values innovation and collaboration, where as a Data Scientist II, you will have the opportunity to work with cutting-edge technologies like machine learning and generative AI in a supportive environment. Our flexible working hours allow you to optimise your productivity while contributing to meaningful projects that enhance scientific discovery and decision-making. With a strong emphasis on employee growth and a culture of trust and respect, we are committed to helping you develop your skills and advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist II in Oxford
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like RELX Group!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Scientist II at RELX Group.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like RELX Group.
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We think you need these skills to ace Data Scientist II in Oxford
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at RELX Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at RELX Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at RELX Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at RELX Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
