About the Role – Data Mining Instructor
Newton School of Technology invites applications for the position of Data Scientist + Instructor – Data Mining within the Computer Science Department. This role is intended for experienced professionals with a strong background in data analysis, pattern discovery, and large-scale data processing who are interested in contributing to academic excellence and student development.
The position combines technical expertise with academic responsibilities, including course design, delivery of lectures and laboratory sessions, and mentorship of students in practical data mining techniques and real-world analytical problem-solving.
The selected candidate will collaborate with academic leadership and industry partners to ensure curriculum relevance, incorporate contemporary industry practices, and promote applied learning outcomes.

Key Responsibilities:
Teaching and Academic Delivery
Design and deliver project-based coursework in Data Mining, covering:
● Data preprocessing, cleaning, and transformation
● Exploratory data analysis and visualization
● Association rule mining and market basket analysis
● Clustering techniques (K-means, Hierarchical, DBSCAN)
● Classification and predictive modeling
● Feature engineering and selection
● Big data analytics using distributed frameworks
● Ethical considerations in data usage and privacy
Curriculum Development:
● Contribute to the design and continuous improvement of the Data Mining curriculum
● Integrate real-world datasets, case studies, and industry tools into course content
Student Mentorship:
● Guide students in building data-driven projects
● Provide structured technical feedback on data analysis methodologies, coding practices, and analytical reasoning
Career Guidance:
● Mentor students on career pathways in Data Science, Analytics, and AI-related roles
● Support students in preparing for internships and full-time employment opportunities
Industry Alignment:
● Stay updated with emerging trends in data analytics, machine learning, and big data technologies
● Incorporate relevant advancements into teaching and learning materials
Collaboration:
● Work closely with faculty members and academic teams to create an integrated and cohesive learning environment
Assessment and Evaluation:
● Design practical assignments, projects, and assessments that reflect real-world industry scenarios
Qualifications and Experience:
● Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field (Ph.D. is desirable but not mandatory)
● Minimum 7 years of hands-on industry experience in Data Science, Analytics, or Data Engineering roles
● Demonstrated experience in extracting insights from large datasets and applying data mining techniques to real-world problems
● Strong conceptual and practical understanding of data analysis, statistical methods, and machine learning foundations
● Demonstrated commitment to teaching, mentorship, and knowledge dissemination
Required Skills:
Technical Competencies
● Expert proficiency in Python programming
● Strong experience with:
○ Pandas, NumPy, and Scikit-learn
○ SQL and relational databases
○ Data visualisation tools (e.g., Matplotlib, Power BI, Tableau – conceptual understanding)
○ Big data tools such as Hadoop or Spark (preferred)
○ Basic understanding of cloud platforms (AWS/GCP/Azure)

Professional Skills:
● Excellent communication and presentation abilities
● Capacity to explain complex technical concepts clearly and effectively
● Strong collaborative and interdisciplinary work approach
● Genuine interest in education, mentorship, and student development

Preferred Qualifications (Good-to-Have):
● Prior teaching experience at the undergraduate or graduate level
● Familiarity with contemporary pedagogical methodologies
● Experience working in analytics-driven startups or product-based technology companies