Data Science Instructor

About Newton:

Newton School of Technology (NST) is a new-age institution redefining technical educationin India. Founded by IIT alumni, NST offers a 4-year B.Tech in Computer Science and AI,focused on hands-on learning and deep industry integration. Within two years, over 93% ofstudents have secured paid internships with companies like Razorpay, SarvamAI, andDRDO, along with global exposure through tech treks to Singapore and Silicon Valley. Ledby a distinguished faculty comprising ICPC World Finalists and ex-professionals from ISRO,Microsoft, MakeMyTrip, and several other leading tech organizations, NST is building ascalable, high-impact model that produces industry-ready talent for the world's mostadvanced technology roles.

About the Role:

We are currently looking for a Data Scientist + Instructor AI/ML to join our ComputerScience Department. This role is ideal for professionals with substantial industryexperience who are passionate about Artificial Intelligence and Machine Learning andcommitted to shaping the next generation of tech talent.The position combines hands-on technical expertise with academic responsibilities,including designing and delivering course content, conducting practical lab sessions, andmentoring students in core Data Science and AI/ML concepts.The ideal candidate will also collaborate with academic leaders and industry partners toensure curriculum relevance, integrate real-world problem-solving, and drive strong learningoutcomes.

Key Responsibilities:

Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML(Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI).

Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculumto reflect current industry tools, techniques, and best practices, incorporating yourprofessional experience and case studies.

Mentor Student Projects: Guide students through hands-on AI/ML projects, providingtechnical direction, code reviews, and feedback based on industry standards.

Guide & Mentor Students: Advise students on developing practical skills,understanding career paths in AI/ML, and preparing for internships and job placements.

Stay Current: Bring the latest AI/ML research, tools, and industry trends into theclassroom.

Collaborate: Work closely with other expert faculty and staff to create a unified andeffective learning experience.

Assess Practical Skills: Design and evaluate assignments, projects, and assessmentsfocused on real-world applications.

Qualifications and Requirements:

Bachelor's or Master's degree in Computer Science, Engineering, Data Science,AI/ML, or related field. (PhD is valued but not mandatory.)

7+years of direct, hands-on professional experience in the tech industry as anAI/ML Engineer, Data Scientist, Research Scientist, or similar role involving AI/MLdevelopment and deployment.

Proven Industry Track Record: Demonstrated experience in building, training, anddeploying machine learning models (including deep learning) for real-world problems.

Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical & deep learning CNNs, RNNs, Transformers), model evaluation, statistics, and awarenessof current research/industry trends.

Passion for Teaching/Mentoring: Ability to explain complex concepts clearly andguide others. Prior mentoring, corporate training, technical workshops, or projectsupervision experience is highly relevant. (Formal academic teaching experience isnot mandatory.)

Required Skills:

Technical: Expert-level Python programming.

Proficiency with data science libraries (Pandas, NumPy, Scikit-learn).

Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch).

Strong SQL and data handling skills.

Understanding of ML Ops practices and tools (Git, Docker, AWS/GCP/Azure).

Knowledge of key AI areas (NLP, Computer Vision, Generative AI/LLMs).

Soft Skills: Strong communication, mentoring ability, collaboration, and a genuinepassion for education.

Good-to-Have:

Prior teaching experience at the undergraduate or graduate level.

Familiarity with modern teaching methodologies and academic