Principal Data Scientist - AI Leader Driving Student Outcomes

TrulyHired; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Risepoint is an education technology company that helps regional universities launch and grow online programs. As Principal Data Scientist, you will lead data science and machine learning initiatives that improve outcomes for students, university partners, and Risepoint.

This hands-on leadership role covers the data science lifecycle—from problem definition and modeling to experimentation, production deployment, and measuring business impact.

Qualifications

• 8+ years of applied data science, machine learning, or related field with technical leadership.
• Strong hands-on experience building predictive models (propensity, churn, retention, engagement...).
• Experience designing and analyzing A/B tests for product decisions.
• Experience taking ML models into production and monitoring performance.
• Experience mentoring data scientists and providing technical direction.

Responsibilities

• Lead data science and AI/ML initiatives from problem definition through measurement.
• Turn ambiguous business problems into data science opportunities with measurable outcomes.
• Own the technical direction of initiatives and collaborate with cross-functional teams to deploy solutions.
• Develop reusable feature engineering and modeling approaches across projects.
• Establish standards for model validation, documentation, and responsible AI.

Skills

Data science leadership

Predictive modeling

A/B testing

Python

SQL

Mentoring

Communication

Model deployment

Education

Bachelor's or Master's in CS/Stats/Engineering

Tools

Databricks

MLflow

Python

SQL

TensorFlow

PyTorch

Job description

Risepoint is an education technology company that helps regional universities launch and grow online programs. As Principal Data Scientist, you will lead data science and machine learning initiatives that improve outcomes for students, university partners, and Risepoint.

This hands-on leadership role covers the data science lifecycle—from problem definition and modeling to experimentation, production deployment, and measuring business impact.