Job Description & How to Apply Below
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:
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.
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