Traditional Data Scientist / Machine Learning Engineer

We are seeking an experienced Data Scientist / Machine Learning Engineer with deep expertise in building predictive models across supervised and unsupervised learning techniques. The ideal candidate should have domain experience in the insurance sector, particularly in underwriting and claims.

Key Responsibilities:

• Develop, deploy, and evaluate machine learning models including classification (Logistic Regression, Decision Trees, Random Forest), regression (Linear, Gradient Boosting, KNN, Neural Nets), and clustering (K-means and others).

• Lead end-to-end data science projects including data preprocessing, EDA, feature engineering, and model performance tuning.

• Build and optimize propensity models for business applications in underwriting and claims.

• Work with NLP techniques for OCR, text extraction, document classification, and summarization.

• Utilize platforms like AWS SageMaker, Databricks, and Python in a hands-on capacity.

Preferred Skills:

• Prior experience with Palantir Foundry and Artificial Intelligence Platform (AIP) is a strong plus.

• Excellent problem-solving and communication skills.