Senior ML Modeler: Production AI & Risk Analytics

Relx Plc; Saint Paul (MN); On-site; USD 105,000 - 175,000; Full time

Benefits offered by this job

Annual incentive bonus

Job summary

LexisNexis Risk Solutions in the United States is seeking a Sr Statistical Modeler to develop and implement analytics and AI solutions that support business and product objectives across the modeling lifecycle.

This role operates in an AI-forward team, collaborating with engineering, product and platform teams, and communicating insights to technical and non‑technical stakeholders while mentoring junior staff.

Qualifications

• Proven Data Science experience with scalable analytics and ML solutions.
• Advanced degree may substitute for part of the required experience.
• Hands-on experience building, evaluating, and deploying predictive models.
• Experience with structured and unstructured data at scale.
• Proficiency in Python or R and common ML libraries.

Responsibilities

• Applies statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex data.
• Develops and maintains data infrastructure connecting internal datasets.
• Trains/mentors junior staff and serves as a subject matter expert.
• Interfaces with clients and cross-functional teams to translate business needs into models.
• Interprets business challenges and recommends best practices to improve products and processes.
• Independently executes complex analytical work within defined scope.

Skills

Data Science

Machine learning

Python

R

SQL

Communication

Cloud computing

Model deployment

Education

Master's degree in a related discipline

Tools

Python libraries (pandas, NumPy, scikit-learn)

XGBoost

PyTorch

SQL

AWS/Azure

Job description

LexisNexis Risk Solutions in the United States is seeking a Sr Statistical Modeler to develop and implement analytics and AI solutions that support business and product objectives across the modeling lifecycle.

This role operates in an AI-forward team, collaborating with engineering, product and platform teams, and communicating insights to technical and non‑technical stakeholders while mentoring junior staff.