Adjunct Professor in Machine Learning

The School of Business and Economics (SBE) at Brandeis University seeks an instructor for BUS/FIN 241a: Machine Learning and Data Analysis for Business and Finance, a 4-credit course in the Fall 2026 semester. This course is structured as a general topics course on machine learning tools, and their implementation through languages such as Python, and the Python packages, Scikit Learn, Keras, TensorFlow, and the Natural Language Toolkit (NLT). The course is oriented heavily to applications in business and finance, giving students the tools needed to survive in the modern data analytics space. It is not intended as a deep theoretical approach to machine learning. Students will finish the class with a basic understanding of how to execute predictive analytic algorithms, as well as rigorously test their performance through various projects. The class meets for 1.5-hours, twice a week in the Fall semester.

Candidates with minimum qualification of a Master’s degree along with relevant professional qualifications and experience with machine learning and data science will be given preference. Candidates with prior teaching experience of relevant/related courses will also be given preference. Interested individuals should submit a cover letter, CV and names and contact information for two references. The deadline for first consideration is July 31, 2026.

The salary range for this position is $10,000 - $12,000, depending on qualifications.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509. 

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").