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Cambium Learning Group

Scientist II

Posted 16 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in USA
Mid level
Remote
Hiring Remotely in USA
Mid level
As a Scientist II, you will design and implement studies for natural language applications, manage cross-program analysis, and ensure coherence in automated scoring systems.
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Cambium Learning® Group is an award-winning educational technology solutions leader dedicated to helping all students reach their potential through individualized and differentiated instruction. Using a research-based, personalized approach, Cambium Learning Group delivers SaaS resources and instructional products that engage students and support teachers in fun, positive, safe and scalable environments. These solutions are provided through Learning A-Z® (online differentiated instruction for elementary school reading, writing and science), ExploreLearning® (online interactive math and science simulations, a math fact fluency solution, and a K–2 science solution), Voyager Sopris Learning® (blended solutions that accelerate struggling learners to achieve in literacy and math and professional development for teachers), and VKidz Learning (online comprehensive homeschool education and programs for literacy and science). We believe that every student has unlimited potential, that teachers matter, and that data, instruction, and practice are the keys to success in the classroom and beyond.

Job Location: US, Remote. Must work and reside within the US for this position.

Job Overview:

As a Scientist II at Cambium Assessment (CAI), you will play an integral part of our 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.

While scientists on the team often develop deep expertise within specific programs or clients for automated scoring, this position emphasizes a cross-program perspective. This position will help maintain coherence and consistency across all programs. The role balances scientific analysis with program-level coordination to strengthen consistency and scalability across CAI’s automated scoring system.

Job Responsibilities:

  • Design and implement studies to obtain, score, model, and analyze results for any of CAI’s current natural language applications, including automated scoring, crisis alert detection, and feedback.

  • Partner with clients to explain the scoring process and support informed decision-making.

  • Own cross-program oversight for Autoscore, maintaining an integrated view across states and administrations to ensure coherence.

  • Drive internal scientific program execution, coordinating calibration, validation, retraining, and monitoring workflows in alignment with administration timelines.

  • Identify, escalate, and track resolution of scoring risks across programs.

Job Requirements:

  • Ph.D. in psychometrics/measurement, NLP, or statistics or related field; or Master’s degree with equivalent applied experience.

  • Demonstrated experience with program management or research–practice partnerships.

  • Experience in k-12 assessment highly preferred.

  • 2+ years working with teams of software developers, NLP scientists, and/or data scientists.

  • Experience in working with client-facing work, including presentations.

To apply for this opportunity, simply click on the “Apply” button and submit a cover letter and resume.

An Equal Opportunity Employer

We are dedicated to fostering a culture that celebrates unique backgrounds, ideas, and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, gender, gender identity/expression, sexual orientation, national origin, protected veteran status, or disability.

Top Skills

Deep Learning
Machine Learning
Natural Language Processing
Statistical Analysis

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