Data Science Manager: Lead AI & Retrieval Systems

Elsevier; Greater London; On-site; GBP 90,000 - 135,000; Full time

Job summary

Elsevier offers a leadership role in Data Science to steer a team delivering intelligent systems that help researchers explore, understand, and act on complex information, blending ML, retrieval, and modern language models.

You will shape a portfolio of high‑impact work, partner with engineering and product, and oversee end‑to‑end delivery while mentoring talent to raise the technical bar across the organisation.

Qualifications

• Extensive experience in data science, ML, or related field.
• Demonstrated success coaching and leading data scientists.
• Proven track record delivering production‑quality AI solutions through a team.
• Deep understanding of ML fundamentals, evaluation, and performance.
• Strong Python skills and ability to guide production‑grade systems.
• Experience with large, complex datasets.

Responsibilities

• Lead, coach, and develop a team of data scientists to grow technically and professionally.
• Set team strategy, priorities, and operating rhythms aligned with product goals.
• Plan and manage capacity across initiatives balancing delivery and investment.
• Establish best practices for experimentation, data quality, and documentation.
• Guide design and delivery of ML/AI systems from problem framing to monitoring.
• Collaborate with engineering to ensure robust, secure production solutions.
• Promote responsible AI and communicate risks and trade‑offs clearly.
• Partner with product and stakeholders to translate needs into measurable outcomes.

Skills

People management

Strategic thinking

Communication

Python

Stakeholder management

Tools

PyTorch

TensorFlow

Scikit-learn

Hugging Face

Elasticsearch/OpenSearch

Job description

Elsevier offers a leadership role in Data Science to steer a team delivering intelligent systems that help researchers explore, understand, and act on complex information, blending ML, retrieval, and modern language models.

You will shape a portfolio of high‑impact work, partner with engineering and product, and oversee end‑to‑end delivery while mentoring talent to raise the technical bar across the organisation.