Pearson
Advanced Associate, Measurement
United States · Full-time
Sponsorship not specified$60k-$70kDetected 5 days ago
PythonJavaC#Data StructuresData AnalysisStatisticsExcelSASResearchCommunicationCollaborationProblem SolvingAdaptabilitySharePoint
Stay score
odds of building a lasting career here
33Risky
Cap-exempt (no lottery)0
Sponsors this role65
Entry-level history0
PERM / green-card track0
Lottery odds (Level I)39
Fits your clock70
Thin sponsorship signal and lottery-bound (~15% per draw). A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- Travel opportunities may be up to 5% and are typically scheduled in advance.
- The full-time salary range for this role is $60,000 - $70,000 annually.
- This position is eligible for Pearson's annual incentive program.
Responsibilities
- Takes direction from Psychometric leads, including Ph.D. level research staff, and follows departmental best practices.
- Prepares, formats, and manages data for use by internal groups.
Requirements
- Bachelor's degree & evidence of success in quantitative courses (e.g., statistics) or software programming/development courses
Compensation
- Compensation at Pearson is influenced by factors including skill set, experience, and location.
Benefits
- Demonstrates openness to learning and applying AI-enabled tools to enhance efficiency and innovation.
Company info
- The Advanced Associate position described here is part of the Pearson Psychometric and Research Services group, which is part of the US School Assessment group and larger Assessment and Qualifications team.
- We are looking for candidates with strong technical and data analysis skills who are able to handle ambiguity and are looking for a challenge.
Apply directly at Pearson →Create a free account for alerts like thisView Pearson immigration profile
This listing is sourced directly from Pearson's careers page and normalized into a canonical job model.