Data Scientist – Predictive Analytics / Predictive ML

Data Scientist – Predictive Analytics / Predictive ML

Location

Schaumburg, IL (Highly Preferred) or Remote for exceptional cases Employment Type: Contract | 3+ months | Strong possibility of extension Focus: Traditional Predictive Machine Learning / Structured & Tabular Data

Role Focus

• Hands-on Data Scientist focused on traditional predictive ML using tabular data
• Strong Python is essential
• Strong experience with tree-based models, feature engineering, data wrangling/data mining, and model evaluation
• Experience handling imbalanced / rare-event datasets is important, such as claims, fraud, credit risk, or similar use cases
• Insurance industry experience is required; P&C Insurance experience is preferred
• Data Engineering is not a core requirement; the focus is more on data preparation, quality, feature engineering, and predictive modeling
• Databricks preferred; equivalent experience with Snowflake, BigQuery, Fabric, Redshift, or Apache Spark is also acceptable

Position Summary

We are seeking a hands-on Data Scientist focused on traditional predictive machine learning using structured, tabular data. The role will develop, evaluate, and support productionization of predictive models for business problems such as risk, claims, fraud, retention, customer behaviour, and loss prediction.

The candidate must have professional experience in the Insurance industry, with P&C Insurance experience strongly preferred.

What the Client is Looking For

The ideal candidate has strong Python skills and hands-on experience with tree-based machine learning, feature engineering, data wrangling, data mining, model evaluation, and imbalanced/rare-event datasets.

Insurance industry experience is required. P&C Insurance experience is preferred

, particularly experience involving claims, loss, fraud, risk, underwriting, pricing, retention, severity, or similar insurance analytics