Description

You will develop and deploy predictive machine learning models within the insurance domain.

Responsibilities

• Build supervised models including Logistic Regression, Decision Trees, Random Forest, Linear Regression, Gradient Boosting, Neural Nets, and KNN.
• Implement unsupervised learning techniques such as K-means and other clustering methods.
• Manage the full model lifecycle from data pre-processing and EDA to modeling and evaluation.
• Develop propensity models specifically for insurance underwriting and claims workflows.
• Apply NLP techniques for OCR-based text extraction, document classification, and summarization.

Required Skills

• 5+ years of experience in machine learning and predictive modeling.
• Proficiency in Python.
• Hands-on experience with AWS SageMaker and Databricks.
• Domain expertise in insurance, specifically within Underwriting or Claims.
• Proven track record of developing propensity models in an insurance context.
• Experience with NLP tasks including document classification and text extraction.
• Bachelor's degree in any field.

Preferred Skills

• Experience with Palantir Foundry and AIP.

Key Skills

Education

Any Gradute