Advanced Specialist, Insights

Advanced Specialist, Insights

PVS is a growing K-12 public virtual school network serving students across the US, committed to delivering high-quality, flexible education to learners of all backgrounds. As we scale our enrollment, we are seeking a data-driven and student-focused Retention Analyst to help us understand, predict, and improve student persistence and engagement throughout the academic year.

 The Advanced Specialist – Insights will sit at the intersection of data, student success, and operations — translating enrollment and engagement data into actionable strategies that keep students on track and connected to our virtual learning community.

What You'll Own

• Build and maintain dashboards and reports tracking student enrollment, attendance, engagement, and attrition trends across grade levels and demographics.

• Develop predictive models to identify at-risk students before they disenroll, enabling proactive outreach by counselors and support staff.

• Partner with Student Success, Enrollment, and Academic teams to design and evaluate retention interventions and re-engagement campaigns.

• Analyze root causes of student withdrawal, including conducting exit surveys and synthesizing qualitative and quantitative data.

• Monitor early warning indicators (login frequency, assignment completion, grade trends) and surface insights to school leadership.

• Present retention findings and recommendations to senior leadership and school administrators on a regular cadence.

• Collaborate with the technology and data engineering teams to ensure accurate, accessible data pipelines from the SIS and LMS platforms.

• Contribute to annual strategic planning by forecasting retention.

About You

• Bachelor's degree in Data Science, Education, Statistics, Business Analytics, or a related field; Master's degree preferred.

• 3+ years of experience in data analysis, preferably within K-12 education, EdTech, or a student-facing organization.

• Proficiency in SQL and at least one analytics or visualization platform (Tableau, Power BI, Looker, or equivalent).

• Experience with predictive modeling and statistical analysis (Python or R a strong plus).

• Strong ability to communicate data findings clearly to non-technical stakeholders.

• Detail-oriented with the ability to manage multiple projects and priorities in a fast-paced environment.

Preferred Qualifications

• Experience working in a virtual or hybrid K-12 school environment.

• Familiarity with Learning Management Systems (LMS) such as Canvas, Schoology, or Brightspace.

• Familiarity with Student Information Systems (SIS) such as PowerSchool, Infinite Campus, or similar platforms.

• Experience building early warning systems or churn prediction models in an educational context.

Ready to make an Impact?

Apply now and help shape what’s next.

Role location: Remote 

Compensation at Pearson is influenced by factors including skill set, experience, and location. 

 
The full-time salary range for this role is $90,000 - $110,000. 
This position is eligible for Pearson’s annual incentive program. Information on benefits can be found here. 

Applications will be accepted through 7/3/26. This window may be extended depending on business needs. 

Pearson is an Equal Opportunity Employer and a member of E-Verify. Employment decisions are based on qualifications, merit and business need. Qualified applicants will receive consideration for employment without regard to race, ethnicity, color, religion, sex, sexual orientation, gender identity, gender expression, age, national origin, protected veteran status, disability status or any other group protected by law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.

If you are an individual with a disability and are unable or limited in your ability to use or access our career site as a result of your disability, you may request reasonable accommodations by emailing TalentExperienceGlobalTeam@grp.pearson.com.