Artificial Intelligence Engineer

1872 Consulting; New York (NY); On-site; USD 95,000 - 140,000; Full time

Job summary

1872 Consulting in New York seeks an AI/ML engineer to uncover meaningful data patterns and transform them into actionable insights using predictive modeling, data mining, and machine learning. You will work with Senior AI/ML Engineers to develop scalable solutions across the enterprise.

The role emphasizes collaboration with business, IT, and Transformation teams, applying techniques like classification, forecasting, and foundational models to improve profitability and operational results.

Qualifications

• Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related disciplines.
• 2+ years of experience with advanced analytics techniques (e.g., decision tree, logistic regression, hierarchical regression, neural network, random forest, etc.).
• 2+ years expert level R or Python analytics experience.
• Hands-on experience with digital and CRM data (structured and unstructured).
• Proven ability to understand, cleanse, and integrate massive disparate data sets and demonstrated familiarity with data modeling workflow.

Responsibilities

• Work alongside Senior AI/ML Engineers to design, develop, and deploy AI/ML solutions with best practices in statistics, machine learning, deep learning, and foundational models to improve the profitability for the company.
• Identify growth opportunities in underwriting, claims processing, risk assessment, and/or customer service through AI/ML augmentation.
• Collaborate cross-functionally with business, IT, and Transformation to drive scalability and impact of the AI/ML solutions.
• Communicate complex AI/ML concepts and findings to business leaders in a clear and concise manner.

Skills

Python

R

Advanced analytics

Education

Master’s degree in Statistics or related field

Job description

*Must be US Citizen or Green Card holder to apply, Full-Time only no Contract or C2C*

About the Job

The AI/ML engineer is responsible for uncovering meaningful data patterns and transforming them into actionable insights by leveraging predictive modeling, data mining, and machine learning algorithms. This includes propensity and uplift modeling, classification models, forecasting, foundation models, and other methodologies.

This individual will work alongside Senior AI/ML Engineers to develop scalable AI/ML solutions and provide data-driven and optimization insights across the enterprise.

Key Responsibilities:

• Work alongside Senior AI/ML Engineers to design, develop, and deploy AI/ML solutions with best practices in statistics, machine learning, deep learning, and foundational models to improve the profitability for the company. Example includes classification models, forecasting, propensity and uplift modeling, foundational model fine-tuning, evaluation, and implementation, etc.
• Identify growth opportunities in underwriting, claims processing, risk assessment, and/or customer service through AI/ML augmentation.
• Collaborate cross-functionally with business, IT, and Transformation to drive scalability and impact of the AI/ML solutions.
• Communicate complex AI/ML concepts and findings to business leaders in a clear and concise manner.

Required Professional and Technical Expertise:

• Must Have Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Operational Research, or related disciplines.
• 2+ years of experience with advanced analytics techniques (e.g., decision tree, logistic regression, hierarchical regression, neural network, random forest, etc.)
• 2+ years expert level R or Python analytics experience
• Hands-on experience with digital and CRM data (structured and unstructured).
• Proven ability to understand, cleanse, and integrate massive disparate data sets and demonstrated familiarity with data modeling workflow.

Preferred Professional Technical Expertise:

• Internship or project experience in AI engineering, machine learning, or a related field, preferably within the insurance or financial services industry.
• Knowledge of actuarial science and insurance-specific data sets.