Data Engineer+ Subject Matter Expert- Data Mining

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.
• 
  
• Required Qualifications:
• A Ph.D. (or a Masters 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.