Principal Data Scientist, Revenue & Pricing Analytics

International; Illinois; On-site; USD 180,000 - 250,000; Full time

Job summary

International's Central Sales Administration seeks a Data Scientist Principal to lead data science across pricing, forecasting, and commercial decisions. This hands-on role defines priorities, guides solution development, and partners with senior leaders to expand data-driven insights.

You will drive enterprise analytics, build scalable data pipelines using Palantir Foundry and Databricks, mentor analysts, and set standards for modeling, deployment, and governance to elevate revenue management.

Qualifications

• Six+ years in analytics, statistics, engineering, IT, data quality or finance.
• Three+ years in leadership, incl. cross-functional initiatives.
• Experience delivering production-grade data science solutions and ML models.
• Strong communication of analytical findings to executives.

Responsibilities

• Define and prioritize data science initiatives aligned with business goals.
• Guide scalable data pipelines, models, and analytical frameworks.
• Lead enterprise analytics solutions using Palantir Foundry and Databricks.
• Translate outputs into decision-support tools influencing pricing and forecasting.
• Mentor data scientists and analysts; promote best practices and adoption.

Skills

Python

SQL

Machine Learning

Leadership

Stakeholder Management

Forecasting

Pricing Analytics

Data Visualization

Education

Bachelor's in CS/Stats/Analytics

Master's degree

PhD in CS/Stats/Analytics

Tools

Palantir Foundry

Databricks

Job description

International's Central Sales Administration seeks a Data Scientist Principal to lead data science across pricing, forecasting, and commercial decisions. This hands-on role defines priorities, guides solution development, and partners with senior leaders to expand data-driven insights.

You will drive enterprise analytics, build scalable data pipelines using Palantir Foundry and Databricks, mentor analysts, and set standards for modeling, deployment, and governance to elevate revenue management.