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-quality

assessment content for an innovative educational publishing/learning initiative.

This role is ideal for professionals who are passionate about making data science

accessible, relevant, and engaging for non-technical learners, particularly students from

Liberal Arts and interdisciplinary backgrounds.

The selected SME will play a critical role in designing pedagogically sound, learner-centric

assessments that evaluate conceptual understanding, interpretation skills, analytical

thinking, and real-world application of data science principles — without requiring

programming or coding exercises.

Key Responsibilities:

The SME will be responsible for creating and reviewing a diverse range of assessment

content aligned with chapter-wise learning objectives.

Assessment Development:

Design and develop high-quality assessment items, including but not limited to:

%CF; Multiple-Choice Questions (MCQs)

%CF; Fill-in-the-Blank (FITB) questions

%CF; Cloze / Drag-and-Drop activities

%CF; Short-answer conceptual questions

%CF; Data interpretation and analytical reasoning questions

%CF; 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 manner
• Pedagogically 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 :

%CF; Strong academic or industry background in Data Science, Statistics, Analytics, Computational Social Science, or related fields

%CF; Experience teaching or developing curriculum for non-technical or interdisciplinary learners.

Prior experience in:

Assessment design

Educational content development

Question bank creation

Excellent 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 universities
• Familiarity with Bloom’s Taxonomy and assessment frameworks Exposure to Liberal Arts, Social Sciences, Humanities, or interdisciplinary education models
• Experience designing assessments for online or digital learning environments
• Seniority Level