Assessment Research Intern

About the Role

We are looking for a highly detail-oriented Assessment Research Intern to support the research and development of our AI-powered Assessment platform. This role is primarily focused on researching, analysing, and systematically mapping assessment methodologies, question frameworks, evaluation models, and skill measurement approaches across different types of assessments. You will research how aptitude, technical, domain, behavioural, and other skill-based assessments are designed and evaluated. You will study question structures, difficulty levels, skill mapping, scoring approaches, assessment patterns, and evaluation methodologies, and convert your findings into structured research frameworks and datasets. Your work will directly contribute to the research foundation behind CareerMaker.ai's Assessment AI, helping the product generate high-quality, relevant, and well-structured assessments. You will work closely with the Product and Assessment teams to translate research findings into structured requirements, frameworks, taxonomies, and knowledge systems for the AI platform.

Key Responsibilities

• Research different types of assessments used for aptitude, technical, domain, behavioural, cognitive, and other skill-based evaluations.
• Study established assessment frameworks, testing methodologies, question formats, evaluation models, and scoring approaches.
• Research how assessment questions are designed, structured, categorised, calibrated, and evaluated.
• Identify and document different question types, question structures, response formats, and assessment patterns.
• Analyse assessment platforms, test repositories, question banks, academic resources, research papers, and other credible sources.
• Compare assessment methodologies across different platforms, domains, and use cases.
• Categorise questions based on skill, topic, sub-topic, difficulty, cognitive level, question type, response type, and other relevant dimensions.
• Identify patterns and common frameworks across large sets of assessment questions.
• Research how difficulty levels are defined, measured, and maintained across different assessments.
• Study how different assessments measure specific skills, competencies, and knowledge areas.
• Build and maintain structured databases, taxonomies, research documents, and assessment frameworks.
• Convert unstructured research findings into structured and machine-readable information that can support AI systems.
• Identify gaps, inconsistencies, ambiguities, and opportunities for improvement in existing assessment methodologies.
• Review research and documentation for accuracy, consistency, completeness, and logical organisation.
• Work with the Product and Assessment teams to translate research findings into requirements for the Assessment AI.
• Continuously update research frameworks and documentation as new assessment methodologies, question formats, and evaluation approaches are identified.

Requirements & Tech Stack

• Strong research and information-gathering skills.
• Excellent reading, comprehension, and analytical abilities.
• Exceptional attention to detail.
• Ability to analyse large amounts of information and identify meaningful patterns.
• Strong ability to compare, categorise, and structure information systematically.
• Strong written English and the ability to communicate research findings clearly.
• Comfortable working with spreadsheets, documents, databases, and structured datasets.
• Ability to work independently and follow a systematic research process.
• Strong organisational and documentation skills.
• Curiosity about assessments, education, AI, testing, learning, psychology, or technology.
• Ability to distinguish reliable and credible information sources from low-quality sources.

Qualifications

• Bachelor's degree in Arts, Humanities, Social Sciences, Psychology, Education, or any other relevant field.
• Prior experience in research, academic research, assessment, documentation, data analysis, or similar work is a plus.
• Familiarity with Excel / Google Sheets, Google Docs, Notion, or similar tools is a plus.
• Candidates with strong research and analytical abilities are encouraged to apply even without prior industry experience.