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Adjunct Faculty-Business Analytics

LASELL UNIVERSITY
Posted 14 days ago, valid for 13 days
Location

Newton, MA, US

Salary

$3,350 per year

Contract type

Full Time or Part Time

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Sonic Summary

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  • Lasell University is seeking an Adjunct Professor for an undergraduate Business Analytics course starting in Fall 2026, requiring a graduate degree in a relevant field.
  • The position involves teaching approximately 6-8 hours per week on campus in Newton, MA, and offers a salary of $3,350 per semester.
  • Candidates must have prior industry experience in data analytics or a related field, along with expertise in analytics tools such as Excel, Tableau, and SQL.
  • Teaching experience at the college level is preferred, and the ability to communicate complex concepts to undergraduate students is essential.
  • This role does not qualify for employment sponsorship and involves preparing students for data-driven roles across the business sector.

Job DetailsJob Location: Lasell University - Newton, MA 02466Position Type: AdjunctEducation Level: Graduate DegreeSalary Range: $3,350.00 - $3,350.00 CommissionJob Category: FacultyAdjunct Professor – Undergraduate Business Analytics  Institution: Lasell University – Department of Data Science  Location: Newton, MA on campus twice a week     Employment Type: Adjunct (per semester)   Start Date: Fall 2026 (September 8, 2026)  This position is approximately 6-8 hours a week This position also does not qualify for any type of employment-sponsorship.    Position Overview The Department of Data Science and Business Management seek an enthusiastic adjunct faculty member to teach an undergraduate course that introduces the conceptual and technical foundations of Business Analytics and Big Data. The instructor will guide students through real‑world analytics practices, data handling, and the use of industry‑standard tools, preparing them for data‑driven roles across the business sector.   Course Description The course provides the conceptual and technical foundations of various aspects of Data Analytics. The purpose is to prepare students with foundation skills in Big Data, a skill widely needed and valued across the business world. Students will explore the analytical process, how data is created, stored, accessed, and how organizations work with data to create environments where analytics can flourish.   Learning Objectives / Outcomes 1. Understand the strategy and technologies of business analytics.  2. Develop foundational skills in Big Data.  3. Describe descriptive, predictive, and prescriptive analytics.  4. Create and interpret data visualizations.  5. Perform data modeling and review data‑mining, simulation, and optimization methods.  6. Use business‑analytics technologies (Excel, Tableau, SQL, etc.).    Key Topics & Skills Students Will Gain - Classification of qualitative vs. quantitative data.  - Construction and interpretation of visual data displays.  - Calculation and discussion of measures of central tendency.  - Evaluation of various analytics types.  - Proficiency with Excel, Tableau, and SQL.  - Understanding of company operations, profiles, and business dynamics.  - Identification of data‑driven business opportunities.  - Bridging business problems with analytical models.  - Communication of technical analysis to both technical and non‑technical audiences.  - Assessment of financial, operational, and ethical implications of data‑driven solutions. - Teach 3 credit hours of the Business Analytics course.  - Prepare and deliver lectures, labs, and assignments aligned with the provided syllabus.  - Design and grade assessments (quizzes, exams, projects).  Qualifications- Required: Master’s degree (or higher) in Business Analytics, Data Science, Statistics, Computer Science, or a closely related field.  - Demonstrated expertise with analytics tools such as Excel, Tableau, SQL, and familiarity with Python/R a plus.  - Prior industry experience in data analytics, consulting, or a related business function.  - Prior teaching or tutoring experience at the college level preferred.  - Ability to convey complex technical concepts clearly to undergraduate students. 




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