SME in Data Science for Liberal Arts

Job Title: SME in Data Science for Liberal Arts

About the Opportunity:We are seeking an experienced and academically strong Freelance Subject Matter Expert(SME) in Data Science for Liberal Arts to support the development of high-qualityassessment content for an innovative educational publishing/learning initiative.This role is ideal for professionals who are passionate about making data scienceaccessible, relevant, and engaging for non-technical learners, particularly students fromLiberal Arts and interdisciplinary backgrounds.The selected SME will play a critical role in designing pedagogically sound, learner-centricassessments that evaluate conceptual understanding, interpretation skills, analyticalthinking, and real-world application of data science principles - without requiringprogramming or coding exercises.

Key Responsibilities:The SME will be responsible for creating and reviewing a diverse range of assessmentcontent aligned with chapter-wise learning objectives.

Assessment Development:Design and develop high-quality assessment items, including but not limited to: Multiple-Choice Questions (MCQs) Fill-in-the-Blank (FITB) questions Cloze / Drag-and-Drop activities Short-answer conceptual questions Data interpretation and analytical reasoning questions Scenario-based and case-study-driven problems

Key Expectations:The ideal candidate should demonstrate the ability to create assessments that are:Conceptually Clear and Accurate: Ensure correctness of content, terminology, and explanations Present concepts in an accessible and learner-friendly mannerPedagogically Strong: Maintain appropriate difficulty progression across chapters and question types. Align assessments closely with stated learning outcomes and instructional goals.Engaging and Application-Oriented: Develop questions that encourage critical thinking and real-world interpretation. Use contextualized examples relevant to Liberal Arts learners.Precise and Unambiguous: Avoid vague wording or multiple interpretations Ensure all questions have clearly defensible answers and instructions.

Desired Candidate Profile : Strong academic or industry background in Data Science, Statistics, Analytics, Computational Social Science, or related fields Experience teaching or developing curriculum for non-technical or interdisciplinary learners.

Prior experience in:Assessment designEducational content developmentQuestion bank creationExcellent written English and attention to detail Ability to simplify technical concepts for diverse learner audiences

Preferred Qualifications:Candidates with one or more of the following will be preferred:Experience working with educational publishers, EdTech organizations, or universitiesFamiliarity with Bloom's Taxonomy and assessment frameworks Exposure to Liberal Arts, Social Sciences, Humanities, or interdisciplinary education modelsExperience designing assessments for online or digital learning environmentsSeniority Level