Data Science Professor

1 week ago

Toronto, Ontario, Canada University of Niagara Falls Canada Full time

We are an innovative and digitally oriented institution located in historic downtown Niagara Falls, Canada's #1 travel destination. Our campus offers a unique blend of metropolitan living and a comfortable community.

About the Faculty and Department

Data analysis is a rapidly emerging profession in Canada. The Master of Data Analytics (MDA) program at the University of Niagara Falls Canada aims to develop big data professionals who can thrive in this high-demand career. Our program focuses on real-world case studies, internships, and capstone projects to equip students with the necessary skills and competencies for a successful data analysis profession.

About the Position

The Master of Data Analytics program invites applications for the position of Assistant Professor, Master of Data Analytics. We seek highly qualified and motivated individuals with a strong background in math, computer science, economics, information technology, or related fields to join our diverse faculty team. The ideal candidate will have an advanced academic background (PhD) and extensive expertise in data science, machine learning, and data analytics. They will be responsible for teaching advanced courses in data science, machine learning, and predictive, prescriptive, and descriptive analysis, as well as mentoring students to achieve career success.

Key Responsibilities
  • Design and deliver comprehensive and engaging lectures on data science topics, covering areas such as machine learning, statistical analysis, and data modeling techniques.
  • Develop teaching plans, notes, and instructional materials to support effective learning.
  • Ability to teach students key concepts in predictive, prescriptive, and descriptive analysis.
  • Develop, supervise, and grade assignments, exams, and student projects.
  • Monitor student attendance, academic progress, and provide feedback on performance.
  • Provide academic counseling and career mentorship to support student growth and success.
  • Actively participate in curriculum development and continuous improvement of course content.
  • Collaborate with other faculty members on research initiatives and interdisciplinary projects.
  • Stay current with trends and advancements in data science and related fields, and integrate this knowledge into course materials.
  • Foster a motivating, student-centered learning environment.
  • Encourage critical thinking and problem-solving amongst students in the application of data science concepts.
Required Qualifications and Experience
  • PhD in Mathematics, Economics, Computer Science, or a related field.
  • Strong knowledge of machine learning techniques and algorithms.
  • Expertise in predictive, prescriptive, and descriptive analysis.
  • Proficiency in at least two of the following software tools: SAS, R, SQL, Python.
  • Strong understanding of data analytics and data modeling techniques.
  • Previous teaching experience at the university level, with a track record of successfully engaging and inspiring students.
  • Previous experience in a research or industry-based data science role is preferred.
  • Experience in the development of machine learning models and working with big data is preferred.
Salary

$120,000 - $150,000 per year, commensurate with experience.

Location

Niagara Falls, Ontario, Canada.

Benefits

We offer a comprehensive benefits package, including health, dental, and vision insurance, as well as a pension plan and paid time off.

Why Work with Us?

The University of Niagara Falls Canada is committed to equity, diversity, and inclusivity within its community. We invite applications from all qualified candidates, particularly those from underrepresented groups. We recognize that applicants may have had obligations outside of work that have negatively impacted their record of achievements. If you choose to disclose these obligations, we will ensure that they do not negatively impact the assessment of your qualifications for the position.

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