Job descriptionJob Title: Part-time Data Science Instructor – Offline Learning Centre Location: Madhapur, Hyderabad Employment Type: Part-time Working Schedule: Flexible (Weekdays and weekends based on batch schedules) About upGrad Founded in 2015, upGrad is Asia's largest integrated Learning, Skilling, Workforce Development, and Placement company. Its offerings include online and hybrid degrees, study abroad programs, certifications, bootcamps, and doctorates for working professionals. Through its B2B arm, upGrad also provides enterprise training, recruitment, and staffing services. With 10M+ learners across 100+ countries, 300+ global university partners, 2,500+ pathway connections, and 20,000+ recruitment partners, upGrad continues to empower careers worldwide. Learn more: www.upgrad.com/offline-centres About the Role We are looking for passionate and experienced Part-time Data Science Instructors to join our Offline Learning Centre in Kolkata. In this role, you will deliver engaging classroom sessions in Data Science, Machine Learning, Deep Learning, Python, SQL, and related technologies to students and working professionals. This opportunity is ideal for industry professionals, corporate trainers, freelancers, or academicians who are passionate about teaching and mentoring while maintaining flexibility in their schedules. Why Join upGrad Offline Learning Centres? 1. Flexible Teaching Schedule Conduct classes during evenings or weekends, allowing you to balance your professional commitments while sharing your expertise. 2. Teach Future Data Professionals Mentor aspiring data scientists through industry-focused curriculum, practical projects, and real-world case studies. 3. Access to upGrad Learning Enjoy complimentary access to upGrad learning programs and continuous opportunities to enhance your own skills. 4. Industry Exposure Work alongside experienced academic teams and contribute to delivering high-quality learning experiences. 5. Professional Network Collaborate with learners, trainers, and industry experts while expanding your professional network. 6. Meaningful Impact Help learners build successful careers in Data Science and Artificial Intelligence through hands-on guidance and mentorship. Key Responsibilities - Deliver engaging offline classroom sessions in Data Science, Machine Learning, Deep Learning, Python, SQL, Excel, and related technologies. - Explain concepts through practical examples, case studies, and hands-on projects. - Mentor learners on assignments, capstone projects, and career development. - Resolve learner doubts and provide academic support throughout the program. - Evaluate assignments, assessments, and project submissions. - Collaborate with Centre Managers and Academic Operations teams to ensure high learner satisfaction. - Stay updated with the latest developments in Data Science, AI, Machine Learning, and Generative AI. - Maintain attendance records and deliver sessions as per the scheduled batches. Skills & Experience - Minimum 2+ years of teaching, training, or industry experience in Data Science, Machine Learning, Artificial Intelligence, or related fields. - Strong programming skills in Python, SQL, and Excel. - Good understanding of Machine Learning and Deep Learning concepts including: - Regression - Classification - Decision Trees - Random Forest - Ensemble Learning - Neural Networks - Natural Language Processing (NLP) - Recommendation Systems - Knowledge of data visualization tools such as Power BI or Tableau is preferred. - Excellent communication, presentation, and mentoring skills. - Comfortable delivering engaging classroom sessions and interacting with working professionals. - Education: BE/B.Tech (minimum); Postgraduate degree preferred. Preferred Candidate Profile - Data Science Trainers - Data Science Instructors - Corporate Trainers - Machine Learning Professionals - AI Trainers - Analytics Professionals with teaching experience - Freelance Trainers - Visiting Faculty - Academic Faculty in Data Science Equal Opportunity upGrad is an equal opportunity employer and values diversity and inclusion. We do not discriminate on the basis of race, religion, colour, national origin, gender, gender identity or expression, sexual orientation, age, marital status, veteran status, disability, or any other protected characteristic. Employment decisions are based on qualifications, merit, and business requirements.
