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 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.

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