Adjunct Faculty - Undergraduate Business Analytics of Data Science

Business Analytics of Data Science 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) Position Overview The Department of Data Science seeks 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 Understand the strategy and technologies of business analytics. Develop foundational skills in Big Data. Describe descriptive, predictive, and prescriptive analytics. Create and interpret data visualizations. Perform data modeling and review data-mining, simulation, and optimization methods. 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. 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. 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. Responsibilities 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). Hold regular office hours and provide timely feedback. Participate in departmental meetings and contribute to continuous course improvement. Compensation Competitive per-credit hour rate, commensurate with experience and qualifications. Payments processed through the university's standard adjunct payroll system. Application Procedure Provide a curriculum vitae highlighting academic credentials and analytics projects. Include contact information for two professional references . Optional: Sample syllabus or teaching material for a comparable analytics course. Lasell University is committed to equal opportunity in every aspect of hiring and employment. Lasell proactively reviews its policies and practices to assure that decisions with respect to every dimension of employment are made without regard to age, color of skin, disability, gender expression and identity, genetic predisposition, marital status, national origin, race, ethnicity, religion, sex, sexual orientation, veteran's status, status as a victim of domestic violence, and all other protected groups and classes under Federal and State Laws and executive orders. To apply, visit https://paycomonline.net/v4/ats/web.php/portal/AE469E23D63EE01425E773C19A546C6B/jobs/597536