Adjunct Professor for Online Data Science Program: Time Series Analysis (ADS-650)

Location
Longmeadow, MA
Posted
Jun 12, 2018
Position Type
Adjunct
Institution Type
Four-Year Institution

Company Description:

When Bay Path opened its doors to students in downtown Springfield, MA in 1897, it had a very clear goal: to provide a practical, affordable, and career-oriented education to meet the needs of companies, organizations, and communities. From the beginning, Bay Path prided itself on being entrepreneurial, constantly pushing the boundaries of the academic experience to fit the student. To start them on the road of success. We still do.

Today, that spirit and philosophy is more important than ever in higher education. At Bay Path, it's not just the number and breadth of undergraduate and graduate programs that defines us-and we have many-but it is our ability to connect the classroom to learning to leadership to experience to career that is at the core of what we do best. We know the work that needs to be done.

Bay Path University, an independent and not-for-profit institution, was named Among Fastest Growing Baccalaureate Colleges by the Chronicle of Higher Education Almanac, and is a member of the Women's College Coalition. With a main campus in Longmeadow, MA and four satellite locations, (East Longmeadow, Sturbridge, Concord, Springfield), Bay Path offers undergraduate, graduate (for women and men) degrees, and professional certificates.

We're committed to preparing our students to navigate a constantly changing world. Whether it is one of our innovative academic programs, groundbreaking online learning platform, or through our Women as Empowered Learners and Leaders initiative, we educate our students in ways that will help them to grow, learn to adapt, and always to flourish. Be part of the change.

We invite you to visit our website at www.baypath.edu where you can learn more about Bay Path University.

Job Description:

Department of Applied Data Science Program at Bay Path University seeks online adjunct faculty to join our experienced and diverse faculty group. Expertise in the following areas is especially desired: Machine Learning, Text Mining, Deep Learning, Time Series, and Database Systems.

  • Job Type: Part-time Adjunct Faculty
  • Class level: Graduate
  • Date class is scheduled to begin: Fall semester 2018
  • Class schedule: Online      
  • Duration of class: 8 Weeks

Course Description: Essential to the analysis of economic and financial data, time series analysis has wide applications and can be applied to any data that has been observed over time. This course introduces both the theory and practice of time series analysis, covering classical topics including stationarity, autocorrelation functions, autoregressive moving average models, partial autocorrelation functions, forecasting, seasonal ARIMA models, power spectra, parametric spectral estimation and nonparametric spectral estimation. The analysis of real-life data and hands-on practice will be emphasized throughout the course. 

Requirements:

  • MS degree in Statistics, Computer Science, Engineering, mathematics or other technical field is required; PhD preferred.
  • Previous higher education teaching experience preferred.
  • Experience and ability to address various aspects of real-world applications is needed, as most of our students work full-time in the industry.
  • If you operate a University owned, leased or personal vehicle at any time while performing your duties you must follow all policies and procedures outlined in the Operations Manual. You must have a valid driver's license and must successfully pass the online safe Driving Course and driving record check at time of hire and annually thereafter.  Additionally, you must report any driving offense, on or off company time, which causes a loss, suspension, or any other change in your license status. You must report this change within one business day of the offense. You can report this change to the Human Resource Department or your direct supervisor. Failure to do so can lead to disciplinary action, up to and including terminations.
  • Ability to adhere to University policies and procedures.
  • Ability to handle confidential information with discretion.
  • Should be committed to a culture of diversity, respect and inclusion; demonstrated ability to build working relationships with people having a wide variety of backgrounds, perspectives, and experiences different from ones' own.
  • General knowledge of the University's mission, purpose, and goals and the role this position plays in achieving those goals.

Additional Information:

Commitment to Diversity and Inclusion

Bay Path University is a diverse community devoted to proactively nurturing a campus-wide culture that promotes and ensures respect, inclusion and safety for all members regardless of race, color, national origin, age, gender, religion, sexual orientation and gender identity, socio-economic background, or physical ability. We are one University that opens our hearts and minds to conversations, to learning and to creating a community that is welcoming of all. Regardless of position, it is expected that each employee will embrace this commitment and demonstrate an attitude of respect toward and acceptance of all members of our community.

Bay Path University will become a smoke- and tobacco-free community as of July 1, 2018.

Application Instructions:

Applicants for this position should attach a cover letter, resume / curriculum vitae, the contact information for four (4) professional, work related references and any other relevant information pertaining to this position and your candidacy.  Please apply online.  Faxes and emails will not be accepted. 

Bay Path University is dedicated to building a culturally diverse and pluralistic faculty committed to teaching and learning in a multicultural environment and strongly encourages applications from minorities, women and all underrepresented backgrounds.  An Equal Opportunity Employer, Bay Path University is committed to fostering diversity in its student body, faculty, and staff. 

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