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 contemporary 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 setting 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 robust 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.

📌 Data Engineer+ Subject Matter Expert Data Mining Pune
🏢 Newton School
📍 Pune