At a Glance
- Tasks: Design and build AI solutions for scientific discovery using machine learning and NLP.
- Company: Join Elsevier, a global leader in information and analytics.
- Benefits: Flexible working hours, wellbeing initiatives, and study assistance.
- Other info: Collaborative team environment with opportunities for career growth.
- Why this job: Make a real impact on research and healthcare with cutting-edge technology.
- Qualifications: Experience in data science, machine learning, and strong Python skills required.
The predicted salary is between 50000 - 70000 £ 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?
About our Team
Our global team supports products in education and electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality.
About the Role
In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale scientific content and data, applying the right techniques to solve complex problems and deliver reliable, production-ready systems. Working closely with cross-functional partners, you will help turn ambiguous challenges into measurable outcomes that improve how researchers discover and use knowledge.
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 behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.
Requirements
- 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.
Work in a Way That Works for You
We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals.
Working Pattern
Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.
About Elsevier
Elsevier is a global leader in information and analytics. We help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information, vast datasets, advanced analytics, and innovative technologies to support visionary science and research, health education, interactive learning, and exceptional healthcare and clinical practice.
At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness technology to support science and healthcare in partnership with the communities we serve. Together, we create possibilities. Join us.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country-specific benefits. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Data Scientist II in London employer: RELX
At Elsevier, we pride ourselves on being an exceptional employer, offering a dynamic work culture that values trust, collaboration, and innovation. Our commitment to employee well-being is reflected in our flexible working hours, comprehensive benefits, and numerous growth opportunities, allowing you to thrive both personally and professionally while contributing to meaningful advancements in science and healthcare.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist II in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving machine learning, NLP, or generative AI. This gives you a chance to demonstrate your expertise and makes you stand out from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data science questions and case studies. Get comfortable explaining your thought process and how you tackle complex problems. Remember, it’s not just about the right answer but how you arrive at it!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Data Scientist II in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Data Scientist II role. Highlight your experience with machine learning, NLP, and generative AI, and show how your skills align with our mission at StudySmarter.
Showcase Your Projects:Include examples of your previous work that demonstrate your ability to tackle complex problems using data science techniques. Whether it's a project on LLMs or a cool AI solution, we want to see what you've done!
Keep It Clear and Concise:When writing your application, clarity is key! Use straightforward language and avoid jargon where possible. We appreciate a well-structured application that gets straight to the point.
Apply Through Our Website:We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at RELX
✨Know Your Tech Inside Out
Make sure you’re well-versed in the machine learning and NLP techniques mentioned in the job description. Brush up on your knowledge of LLMs, Python, and the tools like Pandas and TensorFlow. Being able to discuss these confidently will show that you’re ready to tackle the challenges head-on.
✨Prepare Real-World Examples
Think of specific projects or experiences where you’ve applied data science techniques to solve complex problems. Be ready to explain your thought process, the techniques you used, and the outcomes. This will help demonstrate your practical experience and problem-solving skills.
✨Practice Clear Communication
Since the role involves collaborating with various teams, practice explaining technical concepts in simple terms. You might be asked to communicate your insights to non-technical stakeholders, so being clear and concise is key. Try explaining a complex project to a friend who isn’t in tech!
✨Show Your Passion for Research
Express your enthusiasm for using AI to support scientific discovery. Share any relevant research interests or projects you’ve been involved in. This will not only highlight your passion but also align you with the company’s mission of advancing science and improving health outcomes.
