Data Scientist (Data Mining) & Instructor

Role & Responsibilities

We are currently looking for a Data Engineer + Instructor Data Mining to join our Computer Science Department. This is a full-time academic role focused on data mining, analytics, and teaching/mentoring students in core data science and engineering topics.

Key Responsibilities:

• Develop and deliver comprehensive and engaging lectures for the undergraduate Data Mining, BigData and Data Analytics courses, covering the full syllabus from foundational concepts to advanced techniques.
• Instruct students on the complete data lifecycle, including data preprocessing, cleaning, transformation, and feature engineering.
• Teach the theory, implementation, and evaluation of a wide range of algorithms for Classification, Association rules mining, Clustering and Anomaly Detections.
• Design and facilitate practical lab sessions and assignments that provide students with hands-on experience using modern data tools and software.
• Develop and grade assessments, including assignments, projects, and examinations, that effectively measure the Course Learning Objectives (CLOs).
• Mentor and guide students on projects, encouraging them to work with real-world or benchmark datasets (e.g., from Kaggle).
• Stay current with the latest advancements, research, and industry trends in data engineering and machine learning to ensure the curriculum remains relevant and cutting-edge.
• Contribute to the academic and research environment of the department and the university.

Ideal Candidate

• A Ph.D. (or a Master's degree with significant, relevant industry experience) in Computer Science, Data Science, Artificial Intelligence, or a closely related field.
• Demonstrable expertise in the core concepts of data engineering and machine learning as outlined in the syllabus.
• Strong practical proficiency in Python and its data science ecosystem, specifically Scikit-learn, Pandas, NumPy, and visualization libraries (e.g., Matplotlib, Seaborn).
• Proven experience in teaching, preferably at the undergraduate level, with an ability to make complex topics accessible and engaging.
• Excellent communication and interpersonal skills.

Preferred Qualifications:

• A strong record of academic publications in reputable data mining, machine learning, or AI conferences/journals.
• Prior industry experience as a Data Scientist, Big Data Engineer, Machine Learning Engineer, or in a similar role.
• Experience with big data technologies (e.g., Spark, Hadoop) and/or deep learning frameworks (e.g., TensorFlow, PyTorch).
• Experience in mentoring student teams for data science competitions or hackathons.