Senior ML Engineer + Instructor

About Newton School of Technology (NST)
Newton School of Technology (NST) is a contemporary institution dedicated to redefiningtechnical education in India. Founded by alumni of the Indian Institutes of Technology (IITs),NST offers a four-year B.Tech program in Computer Science and Artificial Intelligence,emphasizing experiential learning and strong industry engagement.
Within two years of its establishment, over 93% of NST students have secured paidinternships with leading organizations such as Razorpay, SarvamAI, and DRDO, along withexposure to global technology ecosystems through academic immersions in Singapore andSilicon Valley.
NST is led by a distinguished faculty comprising ICPC World Finalists and experiencedprofessionals from organizations including ISRO, Microsoft, MakeMyTrip, and otherprominent technology firms. The institution is committed to developing a scalable,
high-impact academic model that equips graduates with the skills required for advancedroles in the technology sector.

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 forexperienced professionals with a strong background in data analysis, pattern discovery, andlarge-scale data processing who are interested in contributing to academic excellence andstudent development.
The position combines technical expertise with academic responsibilities, including coursedesign, 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 toensure curriculum relevance, incorporate contemporary industry practices, and promoteapplied 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, codingpractices, 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 datatechnologies
Incorporate relevant advancements into teaching and learning materials
Collaboration
Work closely with faculty members and academic teams to create an integrated andcohesive learning environment
Assessment and Evaluation
Design practical assignments, projects, and assessments that reflect real-worldindustry 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, orData Engineering roles
Demonstrated experience in extracting insights from large datasets and applyingdata 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 conceptualunderstanding)
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 technologycompanies