Manager Data Science

About our Team:

LexisNexis Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX (www.relx.com), a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case. The company employs over 2,000 technologists, data scientists, and experts to develop, test, and validate solutions in line with RELX Responsible AI Principles (https://stories.relx.com/responsible-ai-principles/index.html).

About the Role:

Are you looking to develop your Data Scientist career?

Do you enjoy coaching others to achieve high standards?

LexisNexis is seeking a Manager, Data Science to lead the development and application of machine learning and generative AI across our end-to-end content ecosystem—from acquisition and conversion through enrichment, storage, and delivery.

This role sits at the center of our transformation toward an intelligent, agentic content platform, partnering closely with engineering, architecture, and product teams to embed AI directly into large-scale content pipelines and platforms.

You will lead a team of data scientists and applied ML engineers to drive innovation across content enrichment, document understanding, metadata systems, and AI-powered product capabilities. The Manager, Data Science will play a central role in shaping how AI transforms our platforms, workflows, and customer experiences.

Responsibilities:

• Leading development of advanced AI Agentic tech.

• Working closely with other data scientists and engineers to design, develop, and deploy AI solutions

• Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs

• Analyzing large datasets to identify patterns and trends that can inform AI development.

• Communicating findings and insights to stakeholders in a clear and concise manner.

• Staying current with the latest AI and machine learning trends and technologies.

• Mentoring junior data scientists and provide guidance on AI and machine learning best practices.

• Driving best practices across our data science functions

• Setting strategy and team direction, with a clear vision for Data Science

• Working with product leaders to apply data science solutions.

• Evaluating and creating new frameworks and defining methodologies and governance

• Leading small- to medium-sized teams (direct or indirect)

• Setting a high bar for model development

Requirements:

• 3+ years of people management experience.

• 7+ years of experience in data science, machine learning, or applied AI

• Have excellent communication skills and the ability to convey information clearly to senior stakeholders

• Highly Desired Skills and Experience:

• Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests

• Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.

• Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.

• Experience with reinforcement learning, prompt engineering, hallucination mitigation

• Strong background in NLP, information extraction, or knowledge systems

• Experience deploying ML/AI solutions into production at scale

• Proficiency in Python and modern ML frameworks

• Experience working with large-scale data platforms (e.g., AWS-based systems)

Preferred:

• Experience with LLMs and generative AI applications (RAG, summarization, document understanding)

• Familiarity with structured + unstructured data pipelines

• Experience in content-rich domains (legal, publishing, knowledge systems)

• Knowledge of taxonomy, ontology, or metadata-driven systems

• Experience integrating ML into complex, multi-stage processing pipelines

U.S. National Base Pay Range: $115,400 - $192,300. Geographic differentials may apply in some locations to better reflect local mar