LexisNexis Intellectual Property Solutions is looking to bring clarity to innovation by delivering better outcomes to the innovation community. This role is to lead a new data science and AI-driven solutions innovation team to develop and scale AI solutions from concept to production.
Requirements
- Deep knowledge of machine learning, natural language processing, generative AI, and modern data/ML architectures.
- Strong grounding in software engineering practices, data pipelines, and MLOps.
- Hands-on ability to contribute to early prototypes alongside a small team.
- Proven track record of delivering greenfield AI/ML solutions into production environments.
- Experience in rapid prototyping, experimental design, and scaling AI systems.
Responsibilities
- Define and execute our AI strategy, transforming complex business challenges into data science-driven solutions that evolve from prototypes into scalable, production-grade AI services.
- Modernize data infrastructure and deploy impactful AI capabilities including generative AI, agentic AI, and deep learning. Each tightly aligned with measurable business outcomes.
- Own the end-to-end lifecycle of AI initiatives from greenfield concept through prototyping, experimentation, and implementation into successful market-ready solutions.
- Rapidly evaluate new AI/ML techniques, architectures, and technologies for practical application.
- Champion responsible AI practices, including transparency, bias mitigation, and model governance.
- Establish technical best practices in experimentation, data pipelines, model development, and deployment, building the foundation for future growth.
- Partner with product managers to shape AI product strategies and make build-vs-buy decisions.
Other
- You will initially lead a very small team (one data scientist and one engineer), working side-by-side with them to prototype, test, and evolve AI solutions from concept to scalable product.
- As the team grows, you will expand its capabilities, establish best practices, and help shape the future of AI innovation across the organization.
- Lead and mentor a small founding team, setting the tone for a culture of innovation, experimentation, and rapid iteration.
- Foster organizational best practices by bridging data science, engineering, and product teams to embed AI across business functions, ensuring alignment through transparent communication and cross-functional collaboration.
- Inspire and develop future team members as the group expands.
- Provide clear communication and insights to senior executives and stakeholders.
- Represent the AI/Data Science team in strategic forums, highlighting impact and progress.
