Machine Learning Engineer

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

Compensation: $135,000 – $175,000 base + bonus + full benefits, (401(k), and more)

About the role and the company.

James Search Group is working closely with a top-tier global property & casualty insurance carrier to identify an AI/ML Engineer to join their enterprise Data and Artificial Intelligence division. This team is driving innovation across the business by developing and scaling AI capabilities that unlock new value and improve decision-making across underwriting, claims, and customer engagement.

As an AI/ML Engineer, you'll collaborate with senior team members to build, refine, and deploy predictive models and intelligent systems. The ideal candidate is skilled in analytics, curious by nature, and passionate about transforming complex data into practical solutions that deliver measurable business impact.

Key Responsibilities:

• Support the development and deployment of AI/ML models—including classification, forecasting, uplift and propensity modeling, and foundational model tuning.
• Collaborate with cross-functional teams to identify use cases where data science can enhance operational efficiency and business performance.
• Partner with business, IT, and strategy teams to ensure AI models are scalable, impactful, and aligned with organizational goals.
• Communicate analytical findings clearly to stakeholders with varying levels of technical knowledge.

Required Qualifications:

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline; Ph.D. a plus.
• Minimum of 2 years’ experience applying advanced analytics methods (e.g., decision trees, logistic regression, neural networks, random forests).
• Proficiency in R or Python for analytics and model development, including work with both structured and unstructured data.
• Proven ability to manage and integrate large, complex datasets and an understanding of end-to-end data modeling processes.
• Strong written and verbal communication skills with the ability to connect technical outputs to business strategy.

Preferred Qualifications:

• Internship or project experience in machine learning, AI engineering, or related roles—especially in insurance or financial services.
• Familiarity with actuarial concepts or insurance-specific data models.
• Enthusiastic about continued learning in AI/ML and staying current with new tools and methodologies.
• Comfortable in a collaborative, fast-paced, and agile working environment.

This is a unique opportunity to grow your career with a highly respected organization investing in next-generation analytics.