LEARNING FACILITATOR, Office of the Provost

Overview

Boston University is launching 3 new online MS programs in Fall 2026 in Computer Science & AI, Software Engineering & AI and Enterprise AI.

Responsibilities

• Provide timely recommendations on course content to instructors and students.
• Respond to student questions and concerns in a timely and efficient manner in alignment with BU’s student-centric culture.
• Hold regular online office hours to meet with individual students and teams.
• Participate/lead open office hours as needed.
• Monitor and engage in student discussion forums on a weekly basis. Monitor and manage student participation in discussion forums.
• Propose and implement delivery initiatives geared toward student engagement.
• Conduct QA activities as part of module pre-launch.
• Manage team issues in coordination with Faculty and CDS leadership.
• Grade assignments.
• Provide detailed feedback to students on their assignments and overall course performance.
• Contribute to daily operations including late submissions checks, publishing grades, etc.
• Report post-launch issues (defects and enhancements as related to course design or Blackboard issues) as per the established process.
• Share feedback for continuous improvement of the course content.
• Identify opportunities and define processes to improve operations.
• Provide regular status updates in the team project management dashboard.
• Other relevant duties that support student learning.

Required Skills

• Must possess a conferred bachelor's degree.
• A graduate degree in Data Science, Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related STEM field is preferred.
• Must demonstrate expertise in at least one of the following three academic areas.
• Experience with Python and data science programming using tools such as NumPy, Pandas, scikit-learn, PyTorch, and Matplotlib.
• Experience with databases and SQL.
• Experience with machine learning and statistical models such as regression, random forests, boosting methods, and neural networks.
• Experience with large-scale data technologies such as Spark, MapReduce, or related big-data platforms.
• Experience with code assistants (e.g., copilot).
• Experience with machine learning and statistical models such as lasso, ridge, random forests, boosting, neural nets.
• Experience with basic optimization techniques (e.g., gradient descent).
• Experience with Python, C, Java.
• Knowledge of systems architecture.
• Experience with databases and SQL.
• Experience with big data tech stacks such as map-reduce, spark, etc.
• Experience with cloud and distributed systems (deploying scalable applications (AWS preferred; GCP/Azure acceptable), containerization, microservices, and observability).
• Experience with data systems (SQL, NoSQL, ETL/streaming pipelines, and ML/AI Ops).
• Experience with responsible and human-centered AI (usability, explainability, and ethical/security considerations in AI-enabled systems).
• Self-motivated with a start-up mindset toward continuous improvement.
• Ability to collaborate effectively in a fully remote environment and quickly learn new tools and technologies.
• Demonstrated interpersonal, communication, and student-support skills.
• Experience managing competing priorities and working with multiple constituencies, including faculty, students, colleagues, and third-party vendors.
• Adaptable and comfortable working in a fluid environment.
• Ability and desire to mentor or coach students, peers, and colleagues.

Required Experience

• Data Science / Enterprise AI Competencies:
• Experience with Python and data science programming using tools such as NumPy, Pandas, scikit-learn, PyTorch, and Matplotlib.
• Experience with databases and SQL.
• Experience with machine learning and statistical models such as regression, random forests, boosting methods, and neural networks.
• Experience with large-scale data technologies such as Spark, MapReduce, or related big-data platforms.
• Experience with code assistants (e.g., copilot).
• Experience with machine learning and statistical models such as lasso, ridge, random forests, boosting, neural nets.
• Experience with basic optimization techniques (e.g., gradient descent).
• Computer Science Competencies:
• Experience with Python, C, Java.
• Knowledge of systems architecture.
• Experience with databases and SQL.
• Experience with big data tech stacks such as map-reduce, spark, etc.
• Experience with cloud and distributed systems (deploying scalable applications (AWS preferred; GCP/Azure acceptable), containerization, microservices, and observability).
• Experience with data systems (SQL, NoSQL, ETL/streaming pipelines, and ML/AI Ops).
• Experience with responsible and human-centered AI (usability, explainability, and ethical/security considerations in AI-enabled systems).
• Software Engineering Competencies:
• AI/LLM-aided and agentic development - using AI coding assistants (e.g., GitHub Copilot, Claude Code, Cursor), prompt engineering, and critically evaluating AI-generated code; familiarity with LLM-powered agents and tool/API integration.
• Modern software engineering - Git/GitHub workflows, code review, testing, debugging, and CI/CD.
• Cloud and distributed systems (deploying scalable applications (AWS preferred; GCP/Azure acceptable), containerization, microservices, and observability).
• Data systems (SQL, NoSQL, ETL/streaming pipelines, and ML/AI Ops).
• Responsible and human-centered AI (usability, explainability, and ethical/security considerations in AI-enabled systems).

Additional Professional Competencies

• Self-motivated with a start-up mindset toward continuous improvement.
• Ability to collaborate effectively in a fully remote environment and quickly learn new tools and technologies.
• Demonstrated interpersonal, communication, and student-support skills.
• Experience managing competing priorities and working with multiple constituencies, including faculty, students, colleagues, and third-party vendors.
• Adaptable and comfortable working in a fluid environment.
• Ability and desire to mentor or coach students, peers, and colleagues.

Desired Competencies

• Experience as a Learning Facilitator, Teaching Assistant, Tutor, or similar instructional role.
• Experience delivering online learning, preferably in a scaled environment.
• Experience working with adult or professional learners.
• Experience with learning management systems and tools such as GitHub Classroom, autograders, or similar instructional technologies.
• Experience building, deploying, or evaluating AI/LLM-based applications.
• Experience creating process documentation, workflows, and best practices.