Principal Data Scientist - Risk & Predictive Modeling

The Corporate; Oakland (CA); On-site; USD 150,000 - 230,000; Full time

Job summary

The Corporate in Oakland, CA is seeking a Principal Data Scientist to lead the design, development and deployment of advanced machine learning models for risk analytics. You will work with cross-functional teams to translate complex data into actionable insights and scalable solutions.

We value strong Python and PySpark skills, experience building UI-focused interfaces, and the ability to mentor others while collaborating with stakeholders across the organization.

Qualifications

• Master’s degree in data-related field or equivalent required.
• 8+ years in Data Science; 2+ years if Doctoral Degree.
• Experience with predictive modeling and risk analytics.

Responsibilities

• Research and apply advanced data science principles to inform business decisions.
• Create data mining architectures and predictive models from diverse data sources.
• Extract, transform, and load data for ML feature engineering.
• Develop defensible predictive or optimization models for risk management.
• Wrangle and prepare data for model development and feature engineering.
• Collaborate with stakeholders to translate data insights into value.
• Present findings to senior management and mentor teammates.

Skills

PySpark proficiency

UI development

Cross-functional collaboration

Education

Master’s Degree in Data Science / ML / CS or equivalent

Doctorate Degree (preferred)

Tools

Python

PySpark

Foundry

AWS

Job description

The Corporate in Oakland, CA is seeking a Principal Data Scientist to lead the design, development and deployment of advanced machine learning models for risk analytics. You will work with cross-functional teams to translate complex data into actionable insights and scalable solutions.

We value strong Python and PySpark skills, experience building UI-focused interfaces, and the ability to mentor others while collaborating with stakeholders across the organization.