Manager Data Science
AI in this role
Are you ready to lead the teams building AI that helps advance science?
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 support products education 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.
This is a hybrid role in Mexico City (Reforma) Our teams operate in a flexible hybrid work model, combining in-person collaboration with remote flexibility. You’ll be expected to participate in regular team meetings and engineering rituals in line with your team’s cadence.
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.
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:
Private Medical, Dental and Vision Plan, coverage for employee and eligible dependents
Savings Fund with company matching contributions
Comprehensive life insurance policy
Grocery voucher
Vacation Bonus, salary supplement based on vacation days taken
Minor medical expenses discount card for minor medical expenses and outpatient services
Access to learning and development resources
Support for personal and work-related challenges through an Employee Assistance Programme
Awards to recognise key service milestones
Time off to support the charities and causes that matter to you
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.
Together, we create possibilities. Join us.


U.S. National Base Pay Range: $238,100 - $442,200. Geographic differentials may apply in some locations to better reflect local market rates.




We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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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.
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How we rate this
Manager Data Science at RELX rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- How do you think about the risk of an AI system in this kind of role failing silently?
- How would you decide a model or AI system is ready to ship?
Adapt your resume
- List these exact terms on your resume: RAG, AI Agents, NLP, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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