"Temporary Online Course Developer Statistical Modeling and Causal Inference"

Posted: 29-Jan-26

Location: Waltham, Massachusetts

Internal Number: R0012721

Location: Remote (U.S.-based only)
Division: Rabb School of Continuing Studies, Brandeis University
Compensation: $3,000 (Approx. 65 hours over 12 weeks)

Brandeis University’s Rabb School of Continuing Studies is seeking a skilled online course developer to design and build a new three credit asynchronous online course titled: Statistical Modeling and Causal Inference

This role is for an experienced academic and curriculum strategist to serve as an Online Course Developer within Brandeis Online’s graduate program. The developer will design and build asynchronous, instructor-facilitated online courses aligned with institutional learning outcomes, accreditation standards, and workforce relevance. This course will cover regression, identification strategies, and causal inference techniques for evaluation of programs, products, and policies.

Responsibilities:

The development of an online asynchronous course entails the creation and/or selection of elements as outlined in the Brandeis Online Course Standards. Required components include a Brandeis-compliant syllabus, instructor-created materials informed by current industry knowledge, learning objects, and applied assignments and assessments aligned to course and program outcomes.

The Developer is responsible for the substantive content and pedagogical strategies of the course and agrees to uphold Brandeis’s academic standards and online course development guidelines.

Throughout the design process, the Developer will collaborate with Brandeis Online staff, adhere to technical requirements for LMS integration, and meet project milestones. Course drafts will be submitted at designated intervals for feedback, and final approval will be contingent upon a comprehensive design review by a Learning Designer, and Brandeis Online.

Qualifications:

• Advanced degree (MS or Ph.D.) in Statistics, Biostatistics, Applied Mathematics, Data Science or a related field.
• Experience in statistical modeling and causal inference, including regression analysis, identification strategies, and methods for addressing bias and confounding in observational data. Ability to apply models to real-world program, product, or policy evaluation contexts.
• Professional experience building regression, generalized linear models, hierarchical/multilevel models, and Bayesian approaches.
• The ability to apply models to real-world datasets and to incorporate statistical software such as SPSS.
• At least 1 year of teaching or training experience (preferably online/asynchronous).
• Minimum 1 year experience developing asynchronous online courses for adult learners in higher education.
• Proficiency with LMS platforms and digital authoring tools.
• Familiarity with analytical tools, collaborative platforms, and interdisciplinary teamwork.
• Strong communication, organization, and independent work skills.
• Familiarity with curriculum design, accreditation standards, and graduate-level rigor.
• Ability to translate interdisciplinary content into engaging, accessible learning pathways.
• Strong writing and editing skills to produce cohesive, learner-centered experiences.

Preferred Experience:

• Experience teaching or developing graduate-level online courses.
• Knowledge of global learner personas and culturally responsive pedagogy.
• Familiarity with Moodle LMS and digital authoring tools (e.g., H5P).
• Familiarity with experiential learning models and employer-aligned curriculum.

Additional Details:

• Fully remote (U.S.-based applicants only; no visa sponsorship).
• 12-week development timeline (~65 total hours).
• Compensation: $3000