- Cultivate an immersive learning environment tailored for post-secondary students, fostering engagement and active participation.
- Design and implement dynamic learning experiences leveraging available resources, integrating diverse teaching methodologies to achieve course objectives effectively.
- Streamline lesson planning, assignments, and class activities, ensuring alignment with course objectives and institutional standards.
- Facilitate engaging class discussions to stimulate collaboration, communication, and critical thinking among students.
- Encourage intellectual exploration, guiding students to hone their analytical and reasoning skills.
- Spearhead the exploration and application of market leading technologies and lead students in research and development projects.
- Provide personalized academic support through tutoring and counseling, offering constructive feedback and motivation as needed.
- Extend academic assistance beyond the classroom through scheduled office hours, email correspondence, and group study sessions.
- Actively contribute to departmental and faculty meetings, staying abreast of relevant developments and responsibilities.
- Pursue ongoing research endeavors within the field, deepening expertise and enhancing teaching efficacy.
Requirements Education and Experience
- A certificate, diploma or post-secondary degree relevant to the subject matter and two years of full-time work experience in a career occupation relevant to the subject matter of the course, OR
- 10 years of full-time work experience in a career occupation relevant to the subject matter of the program.
- A master's degree in science or in an appropriate discipline is considered an asset.
- Experience in (including but not limited to) data integration, data management, data warehousing and reporting, and big data analytics.
- Experience with building predictive and prescriptive models in a business setting (i.e., regression, decision trees, deep learning etc.).
- Working knowledge of Learning Management System (LMS); Canvas, is an asset.
- Previous teaching experience at a college or a university level is an asset.
- Criminal background check will be required if selected.
- Proficiency in statistical methods and tests (t-tests, chi-square tests, ANOVA).
- Understanding of distributions, hypothesis testing, and probability.
- Proficiency with tools like Tableau, Power BI, and D3.js.
- Ability to create effective and visually appealing data visualizations.
- Strong SQL skills for data extraction and manipulation.
- Experience with query optimization and complex joins.
- Proficiency in Python or R for data manipulation and analysis.
- Knowledge of data analysis libraries such as pandas, NumPy, and ggplot2.
- Techniques for handling missing data, outliers, and ensuring data quality.
- Data wrangling and transformation using tools like Excel, OpenRefine, or Python/R libraries.
- Ability to translate business requirements into data-driven solutions.
- Strong analytical skills to interpret data and generate insights.
- Familiarity with supervised and unsupervised learning techniques.
- Basic implementation of regression, classification, and clustering algorithms using Python/R.
- Techniques for feature engineering, normalization, and data transformation.
- Handling imbalanced datasets and performing cross-validation.
- Understanding of evaluation metrics like accuracy, precision, recall, F1 score.
- Basic hyperparameter tuning and model validation techniques.
- Expertise in relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra).
- Advanced SQL for complex queries, indexing, and performance tuning.
- Designing and implementing robust ETL pipelines.
- Proficiency with ETL tools such as Apache NiFi, Talend, Informatica.
- Proficiency in Hadoop, Spark, Kafka, and other big data frameworks.
- Understanding of distributed computing and data processing.
- Strong skills in Python, Java, and SQL.
- Scripting with Bash or other shell languages for automation.
- Experience with AWS (Redshift, S3), Azure (Data Lake, Synapse), Google Cloud (BigQuery).
- Familiarity with cloud data services and infrastructure management.
- Designing and implementing data models for efficient storage and retrieval.
- Understanding of data warehousing and data lakes.
- Knowledge of system design principles and best practices for scalability and reliability.
- Experience with microservices architecture and API development.
- Implementing data security measures and ensuring compliance with regulations.
- Knowledge of encryption, masking, and data governance.
- Proficiency in administering enterprise Linux environments.
- Previous curriculum and program development experience is considered an asset.
- Proven experience supervising students, providing support and feedback in constructive and meaningful manners is highly desirable.
- Excellent written and oral communication skills.
- Ability to communicate complex information to students both orally and written in an understandable manner.
- Demonstrate a commitment to diversity, equity, and inclusion when interacting with students and colleagues.
- Capable of working independently as well as being part of a team.
- Being able to work under pressure/fast-paced environment and deliver on scheduled deadlines.