Senior Manager, Automated Scoring

Cambium Learning Group

5d•Remote

About The Position

As the Senior Manager of Automated Scoring, you will play an integral part of the machine learning team, which consists of mathematicians, data scientists, psychometricians, linguists, and software engineers. Our team focuses on natural language applications in educational measurement, with key foci in the automated scoring of student responses for both summative and interim assessments, automated feedback for formative assessments, and automated alerting of disturbing content in student responses. Our team uses state-of-the-art deep learning tools and models different modalities (e.g., speech, text) and is responsible for both prototyping and deploying engines and models. This position will lead a team of scientists on data design and analytic efforts for our suite of products, work closely with internal and external stakeholders to ensure we meet their needs, present at planning and technical advisory meetings, write technical reports and contribute to our growing body of research by publishing, and contribute to enhancements of existing products or to new products. This position will work closely with the other leads in the machine learning team on developing new applications for automated scoring methods.

Requirements

Ph.D. in psychometrics/measurement, NLP, or statistics or related computational field
10+ years professional experience in k-12 assessment
8+ years working with teams of software developers, NLP scientists, and data scientist
Experience in working with client-facing work, including presentations
Established publication record in NLP applications in k-12 assessment

Responsibilities

Support CAI’s innovation in natural language applications in support of our mission to improve educational outcomes for our students and educators. This includes automated scoring in large scale assessment programs (for writing, speech and other areas of educational measurement), detection of crisis alert content in student writing and the use of ML for feedback in student writing.
Support CAI’s emerging product portfolio for products that employ state of the art machine learning methods that provide solutions to real world problems in K-12, higher education and other related domains.
Contributes to R&D agenda and sets priorities for the automated scoring team
Drive and provide mentorship to a team of Scientists
Design and implement studies to obtain, score, model, and examine results for any of CAI’s current natural language applications, including automated scoring, crisis alert detection, and feedback.
Pursue applied research to actively publish and represent CAI’s leadership in this area
Present at planning and technical advisory committee meetings