AI/ML Engineer — Scalable Predictive Models for Insurance

James Search Group; New York (NY); On-site; USD 135,000 - 175,000; Full time

Job summary

James Search Group is seeking an AI/ML Engineer to join their enterprise Data and AI division in New York. You will develop, refine, and deploy predictive models and intelligent systems across underwriting, claims, and customer engagement.

Collaboration with senior team members will push innovative analytics into practical business value. The role emphasizes building scalable data solutions, communicating insights to stakeholders, and applying advanced techniques to real-world insurance data.

Qualifications

• Requires Master’s degree or higher in a quantitative field.
• Ph.D. is a plus for the role.
• 2+ years applying advanced analytics methods and predictive modeling.

Responsibilities

• Support development and deployment of AI/ML models across classification, forecasting, uplift and propensity modeling.
• Collaborate with cross-functional teams to identify data science use cases improving efficiency and performance.
• Partner with business, IT, and strategy to ensure scalable, impactful models aligned with goals.
• Communicate analytical findings clearly to stakeholders with varied technical knowledge.

Skills

Decision trees

Logistic regression

Neural networks

Random forests

Analytics

Data modeling

Communication

Python

R

Education

Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field

Ph.D. is a plus

Tools

Python

R

Job description

James Search Group is seeking an AI/ML Engineer to join their enterprise Data and AI division in New York. You will develop, refine, and deploy predictive models and intelligent systems across underwriting, claims, and customer engagement.

Collaboration with senior team members will push innovative analytics into practical business value. The role emphasizes building scalable data solutions, communicating insights to stakeholders, and applying advanced techniques to real-world insurance data.