Extract data from SQL and NoSQL systems (Snowflake, MongoDB, and other databases) to support psychometric analyses and operational reporting.
Ensure data integrity through rigorous validation, transformation, and documentation practices.
Analyze data related to item and test content, quality, and performance using statistical and psychometric methods.
Support psychometricians with advanced analyses, including IRT modeling, reliability studies, norming, and other specialized methodologies.
Validate assessment logic to confirm that scoring rules, branching, and performance assumptions operate as intended.
Define, calculate, and track assessment quality and performance metrics to ensure consistency and accuracy across programs.
Design and implement research studies, simulations, and data mining projects to investigate assessment behavior and support continuous improvement.
Communicate analytical findings through clear written reports, data visualizations, dashboards, and presentations tailored to both technical and non‑technical audiences.
Maintain up‑to‑date knowledge of statistical analysis techniques, psychometric best practices, and modern data engineering workflows.

Bachelor's degree in statistics, mathematics, data science, or a related field from four-year accredited college or university, and
Minimum 6 years’ experience implementing analysis and testing plans and defining and tracking metrics, OR Equivalent combination of education and experience
Extensive database management experience in both structured (SQL) and unstructured (NoSQL) databases especially MongoDB.
Ability to manipulate and analyze data in SAS, r, and Python.
Exceptional attention to detail.
Demonstrated ability to work well within a team and cross functionally.

Psychometric Data Analyst II

Key skills