Job ID
23597

Please Note: Visa sponsorship is not available for this position now or in the future. The Data Scientist - Learning Analytics is required to work on campus in Cambridge, MA 4 days/month or more, depending on the needs of the team.

Position Overview:

Data Scientist – Learning Analytics, Open Learning (OL), to leverage experience with data-science tools and research on pedagogy and learning data to help faculty, course teams, and staff design and assess digital learning experiences.

Principal Duties and Responsibilities (Essential Functions):

Extract meaningful and actionable insights from complex datasets about learners, courses, and their contexts in order to understand and optimize learning and the environments in which it occurs.

Responsibilities include:

  • Effectively collaborating with faculty, course teams, and colleagues on learning analytics, course design, and assessment;

  • Designing and conducting experiments on pedagogy and course content;

  • Building and analyzing statistical models pertaining to learning and content, and providing data-science, statistics, and application/dashboard support to stakeholders;

  • Actively engaging faculty, course team, colleagues, and other stakeholders to drive innovation at Open Learning and across MIT in the use of data-driven learning analytics;

  • Disseminating results to foster broader experimentation and adoption of successful strategies;

  • Performing other duties as needed.

Reports to Open Learning’s Assistant Director for Learning Sciences and Teaching in Residential Education.  Works closely with the Project Manager for Educational Systems and Services and others in Open Learning and across MIT.

Supervision Received:

Assistant Director for Learning Sciences and Teaching in Residential Education

Supervision Exercised:

None other than occasional students

Qualifications & Skills:

MINIMUM REQUIRED EDUCATION AND EXPERIENCE:

REQUIRED:

  • Bachelor's degree in related field with education research methods and statistical analysis required. Master's degree preferred

  • Minimum 7 years of experience

  • Demonstrated effectiveness consulting with stakeholders to assess learning analytics needs and recommending high-impact projects

  • Demonstrated proficiency in applying learning sciences and learning analytics knowledge to the design and implementation of research-based teaching practices

  • Highly skilled in Python (preferred) or R, has a working knowledge of SQL

  • Proficiency with modern data science tools such as jupyter notebooks

  • Ability to collect, process and analyze data from different sources, using relevant APIs and other methods

  • Experience handling access, data, & billing in a major cloud provider (e.g., GCP, AWS, Azure)

  • Demonstrated ability to work effectively both as part of a team and independently and to collaborate effectively with individuals with diverse skills at all levels of an organization

  • Excellent oral and written communication skills

  • Ability to work on multiple projects concurrently, producing initial results quickly then iterating; the flexibility necessary to work in a highly fluid organization

 

PREFERRED EDUCATION AND EXPERIENCE:

  • Familiarity with Google Cloud Platform (e.g., Google BigQuery) is a plus;

  • Familiarity with Canvas LMS and/or the edx/OpenEdx eco-system, and their data organization is a plus.

 

Employment is contingent upon the satisfactory results of a background check.

The salary range for this position is $110,000 - $125,000. Final salary is determined by MIT’s compensation team based on the skills and experience of selected candidate.

Visa sponsorship is not available for this position now or in the future.

This is a hybrid position.  The Data Scientist - Learning Analytics is expected to work on campus in Cambridge, MA 4 days/month or more, depending on the needs of the team.

 

MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.