At a Glance
- Tasks: Lead a team to innovate AI-driven search and evaluation systems.
- Company: Join Elsevier, a leader in science and healthcare analytics.
- Benefits: Enjoy flexible work, wellbeing initiatives, and career development opportunities.
- Other info: Collaborative environment focused on advancing knowledge and improving lives.
- Why this job: Make a real impact on global health and research through cutting-edge technology.
- Qualifications: 6+ years in data science with leadership experience and strong Python skills.
The predicted salary is between 36000 - 60000 € per year.
Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. As the landscape of science and healthcare evolves, we are pioneering intelligent discovery experiences — from Scopus AI and LeapSpace to ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines.
About the role: We are seeking a Search and Evaluation Data Science Team Lead to join Elsevier’s Platform Data Science organisation — the team driving enterprise-scale AI, retrieval, and evaluation innovation across Elsevier’s global platforms. This role will lead a group of applied scientists advancing lexical, vector, and hybrid retrieval systems; designing robust evaluation frameworks; and shaping the foundation of Elsevier’s next-generation search and AI ecosystem.
Key responsibilities:
- Collaborate on core platform services powering knowledge graphs, semantic enrichment, and generative interfaces that underpin Elsevier’s AI products in science, health, and life sciences.
Data Science & Evaluation
- Advance Elsevier’s knowledge graph and metadata integration strategy, linking research and health data for more context-aware retrieval.
Requirements:
- 6+ years of experience building and evaluating search, ranking, or retrieval systems, including 2+ years in a leadership or senior technical role.
- Strong programming proficiency in Python, with hands-on experience in PyTorch, Hugging Face, LangGraph or Haystack.
- Experience deploying retrieval-enhanced LLMs and hybrid retrieval pipelines in production environments.
- Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef).
- Strong communication and stakeholder management skills, with the ability to bridge data science, engineering, and product domains.
- Prior experience in academic publishing, research intelligence, or enterprise-scale AI systems.
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. We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: As 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 Team Lead, Search & Evaluation employer: LexisNexis Risk Solutions
Elsevier is an exceptional employer that prioritises employee well-being and professional growth, offering a supportive work culture enriched with numerous wellbeing initiatives, shared parental leave, and opportunities for continuous learning. As a leader in information and analytics, working here means contributing to meaningful advancements in science and healthcare while enjoying a healthy work/life balance in a collaborative environment that values innovation and societal impact.
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Team Lead, Search & Evaluation
✨Tip Number 1
Network like a pro! Reach out to folks in the data science community, especially those who work at Elsevier or similar companies. Attend meetups, webinars, and conferences to make connections that could lead to job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to search and evaluation systems. Use platforms like GitHub to share your code and demonstrate your programming prowess in Python and other relevant tools.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of retrieval systems and AI technologies. Be ready to discuss your past experiences and how they relate to the role of Data Science Team Lead. Practice common interview questions with a friend!
✨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 Elsevier.
We think you need these skills to ace Data Science Team Lead, Search & Evaluation
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Science Team Lead role. Highlight your experience with search and retrieval systems, and don’t forget to showcase your leadership skills. We want to see how you can contribute to our mission!
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 your background aligns with our goals at Elsevier. Let us know what excites you about the role and our innovative products.
Showcase Relevant Projects:Include any relevant projects or experiences that demonstrate your expertise in Python, PyTorch, or hybrid retrieval systems. We love seeing practical examples of your work, so don’t hold back on the details!
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and keep track of it. Plus, you’ll get to explore more about our culture and values while you’re there!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Tech Inside Out
Make sure you brush up on your programming skills, especially in Python. Be ready to discuss your experience with PyTorch, Hugging Face, and any hybrid retrieval systems you've worked on. They’ll want to see how you can apply these tools in real-world scenarios.
✨Showcase Your Leadership Skills
Since this role involves leading a team, be prepared to share examples of your leadership experience. Talk about how you've managed projects, mentored team members, or collaborated across departments. Highlight your ability to bridge the gap between data science and engineering.
✨Understand the Business Impact
Familiarise yourself with Elsevier’s mission and how their products impact research and healthcare. Be ready to discuss how your work in data science can contribute to their goals of advancing discovery and improving health outcomes.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-time. Think about challenges you've faced in building or evaluating search systems and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
