Measurement Data Analyst I — Research & Insights

Pearson; Boston (MA); On-site; USD 60,000 - 70,000; Full time

Job summary

Pearson is seeking an Advanced Associate in Measurement to support large-scale assessment programs. You will analyze data, apply quantitative methods, and collaborate with psychometric leads and experts.

The role emphasizes handling data responsibly, adhering to best practices, and learning AI-enabled tools. Travel may occur up to 5% as projects demand, with a focus on delivering quality analyses under tight timelines.

Qualifications

• Bachelor's degree with success in quantitative courses or software programming/development courses.
• Experience with data analysis and psychometric concepts preferred.
• Familiarity with data structures and office software.
• Experience with SAS, Python, or other data analysis tools.
• Knowledge of software development principles and version control is beneficial.
• Strong communication and collaboration skills, including remote work.

Responsibilities

• Takes direction from psychometric leads and follows departmental best practices.
• Under supervision, conducts analyses using exploratory techniques such as data mining and statistics.
• Executes and debugs existing analysis tools according to specifications.
• Works with a variety of data structures and moderately complex files.
• Evaluates data suitability and outcomes for analysis purposes.
• Prepares, formats, and manages data for internal use; collaborates with SMEs and tech staff.
• Openness to learning and applying AI-enabled tools to enhance efficiency.
• Meets schedules while working independently; travel up to 5%.

Skills

Data analysis

Python

SAS

R

Java

Microsoft Excel

Communication

Education

Bachelor's degree

Tools

SAS

Python

C#

R

Java

Microsoft 365

Job description

Pearson is seeking an Advanced Associate in Measurement to support large-scale assessment programs. You will analyze data, apply quantitative methods, and collaborate with psychometric leads and experts.

The role emphasizes handling data responsibly, adhering to best practices, and learning AI-enabled tools. Travel may occur up to 5% as projects demand, with a focus on delivering quality analyses under tight timelines.