Principal Data Scientist

Role Description

In this role, you will lead the technical outcomes and rigor for both the intelligence layer that powers how Risepoint engages with students at every stage of their journey and the data engineering backbone beneath it, serving as the principal point of accountability for the domain. You will define and lead end-to-end initiatives—from strategy and architecture through cross-functional implementation and measurable outcomes—that directly shape retention, engagement, and enrollment results for thousands of students across more than 100 university partners.

You will shape and execute the technical vision for and delivery of the “Next Best Experience” platform: the predictive engine that turns raw behavioral signals into personalized, timely outreach.

You will build alignment across Product, Engineering and business stakeholders on technical approaches. Your decisions, technical expertise and data-driven recommendations will determine who gets reached, when, and how—translating data science into student outcomes that help working adults succeed in programs that change their lives.

You will bring our mission to life by leading initiatives that make the student journey smarter and more human at the same time. Every initiative you own—from scoping a churn-risk model through deploying it into production and measuring its downstream impact—translates directly into a real person getting the support they need before they fall through the cracks. By driving cross-functional alignment and accountability across Product, Engineering, and CX teams, you will help Risepoint’s university partners serve more students more effectively.

Qualifications

• A proven track record of delivering measurable consumer and business impact through AI/ML initiatives.
• Experience operating as a principal-level technical leader or domain authority.
• 8+ years in applied machine learning or data science, ideally in education, consumer tech, personalization, or a complex behavioral domain.
• Strong background in predictive analytics, recommendation systems, and experimentation.
• Deep expertise in Python and SQL; proficiency with ML libraries.
• Principal-level data engineering experience.
• Hands-on experience taking models to production and operating them there.
• Proficiency with production automation tooling.
• Strong grounding in data quality, governance, lineage, and observability practices.
• Excellent communicator and influencer across technical and non-technical audiences.
• Bachelor’s or Master’s degree in a technical discipline.

Requirements

• Set direction for and lead AI/ML initiatives end-to-end.
• Own accountability for delivering measurable business outcomes from each initiative.
• Drive alignment and decision-making across teams.
• Identify and scope net-new AI/ML opportunities.
• Manage relationships with key vendors and software providers.
• Build and deploy predictive models.
• Lead the design and implementation of “next best action” logic.
• Architect, build, and own scalable, reliable data pipelines.
• Automate production workflows with orchestration tools.
• Design and lead A/B testing programs.
• Mentor data scientists and engineers across the team.

Benefits

• Equal-opportunity employer.
• Supports a diverse and inclusive workforce.