Role: Data Scientist (Traditional)

Location: Atlanta

Experience: 6 10 Years

Short Summary

Strong traditional ML engineer. Should know supervised (Classification/Regression) and unsupervised models like clustering, with full end-to-end hands-on experience (data pre-processing, EDA, modeling, evaluation). Insurance (Underwriting/Claims) background preferred, Python required, and experience with AWS Sagemaker and Databricks is a plus.

Responsibilities

• (Classification/Regression) and unsupervised/clustering ML models.
• Should understand how these model algorithms work.
• Hands-on experience around predictive models (data pre-processing, EDA, modeling, evaluation).
• Logistic Regression, Decision Tree, Random Forest for classification.
• Linear, Gradient Boosting, Neural Nets, KNN for regression.
• K-means and other clustering techniques.
• Should have insurance domain experience (Underwriting/Claims).
• Must have developed propensity models within insurance business.
• Python proficiency.
• AWS SageMaker, Databricks experience preferred.
• Familiarity with OCR-based text extraction, document classification, document summarization.
• Palantir Foundry and AIP experience is a plus.