At a Glance
- Tasks: Lead AI and data science strategy to create impactful, scalable solutions.
- Company: Global leader in information and analytics, advancing science and healthcare.
- Benefits: Flexible working hours, wellbeing initiatives, study assistance, and sabbaticals.
- Other info: Collaborative culture with a focus on trust, respect, and innovation.
- Why this job: Shape the future of AI while making a real difference in healthcare.
- Qualifications: Experience in data science, AI/ML, and leading technical teams.
The predicted salary is between 70000 - 90000 £ per year.
Are you motivated to shape AI and data science strategy that drives meaningful impact across products, customers, and business outcomes? Would you enjoy leading teams to build advanced AI systems that power knowledge discovery and innovation at scale?
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 define and lead AI and data science strategy across machine learning, NLP, search, and generative AI to deliver impactful, scalable solutions. You will guide teams through the full lifecycle of AI systems, from experimentation to production, while aligning work to product goals and customer needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation.
Responsibilities
- Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities.
- Lead and develop high-performing teams by coaching talent, setting priorities, fostering scientific rigor, and building an inclusive, collaborative culture.
- Deliver advanced AI and knowledge-discovery systems across the full lifecycle, from experimentation through production, including LLMs, RAG, search, and domain-enriched AI solutions.
- Drive evaluation and AI quality by establishing robust frameworks, metrics, experimentation practices, and responsible AI standards.
- Influence across product, technology, and business by partnering with cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact.
Requirements
- Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience.
- Strong technical expertise across modern data science methods, including machine learning, experimentation, deep learning, generative AI, and production AI systems.
- Hands-on experience delivering AI-powered products, including LLMs, RAG, semantic search, embeddings, agentic workflows, and knowledge-driven systems.
- Proven success leading and developing technical teams in complex product, platform, or research environments.
- Experience working with large, complex datasets and building scalable, maintainable, production-ready AI/ML systems.
- Strong people leadership, prioritization, communication, and stakeholder management skills, with the ability to turn ambiguity into clear strategy and measurable outcomes.
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 the Business
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 and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
Data Science Lead/Manager in London employer: Elsevier
At Elsevier, we are committed to fostering a dynamic and inclusive work culture that prioritises trust, collaboration, and innovation. As a Data Science Lead/Manager, you will have the opportunity to shape impactful AI strategies while leading high-performing teams in a flexible environment that promotes work-life balance and personal growth through various wellbeing initiatives and professional development opportunities. Join us in making a meaningful contribution to global health outcomes and advancing science for a better future.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Lead/Manager 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 related to AI and data science. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science questions and case studies. Practice explaining your thought process clearly, as communication is key when leading teams and influencing stakeholders.
✨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, it shows you're genuinely interested in joining our team at StudySmarter.
We think you need these skills to ace Data Science Lead/Manager in London
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter to highlight your experience in AI, data science, and leadership. We want to see how your skills align with our mission to drive meaningful impact across products and customers.
Showcase Your Achievements:Don’t just list your responsibilities; share specific examples of projects you've led or contributed to that demonstrate your expertise in machine learning, NLP, or generative AI. We love seeing measurable outcomes!
Be Authentic:Let your personality shine through in your application. We value trust and collaboration, so showing us who you are and how you work will help us understand if you’re a good fit for our team culture.
Apply Through Our Website:We encourage you to submit your application directly 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 Elsevier
✨Know Your AI and Data Science Stuff
Make sure you brush up on the latest trends in AI, machine learning, and NLP. Be ready to discuss your hands-on experience with LLMs and generative AI, as well as how you've tackled complex datasets in the past.
✨Showcase Your Leadership Skills
Prepare examples of how you've led teams in previous roles. Highlight your ability to coach talent and foster a collaborative culture. They’ll want to see that you can inspire and guide others towards achieving product goals.
✨Align with Their Values
Familiarise yourself with the company’s values like trust, respect, and collaboration. During the interview, weave these values into your responses to show that you’re not just a technical fit but also a cultural one.
✨Prepare for Stakeholder Engagement
Think about how you’ve influenced senior stakeholders in the past. Be ready to discuss how you translate technical insights into business impact, as this role requires strong communication and stakeholder management skills.
