🎯 Role Overview
We are seeking a Data Science Faculty / Trainer with a proven blend of industry execution (IT or service-based projects) and academic delivery (EdTech or corporate training) .
You will be responsible for delivering end-to-end learning programs in Data Science, Machine Learning, AI, and Generative AI , while also integrating real-world IT project experience into your sessions.
The ideal candidate is both a hands-on practitioner and an educator — capable of mentoring learners, translating enterprise-grade solutions into simple concepts, and driving measurable learning outcomes.
📘 Key Responsibilities
- Deliver instructor-led sessions on :
- Python for Data Science
- Statistics & Probability
- Exploratory Data Analysis (EDA)
- Machine Learning (Supervised & Unsupervised)
- Deep Learning (ANN, CNN, RNN, LSTM)
- Natural Language Processing (NLP)
- SQL, Power BI, Tableau
- Cloud AI tools (AWS, Azure, GCP optional)
- Design, develop, and update course content, assignments, and capstone projects.
- Conduct hands-on lab sessions and case study-driven workshops .
- Mentor students in projects and guide them through end-to-end ML lifecycle.
- Evaluate students’ progress through quizzes, assignments, and viva sessions.
- Stay updated with current industry trends, tools, and frameworks in AI / ML.
- Support placement readiness through technical mock interviews and portfolio reviews.
- Collaborate with academic teams to enhance learning delivery and student experience.
🧩 Required Skills and Competencies
Proficiency in Python, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn .Strong knowledge of Statistics, Probability, Linear Algebra, and Data Modeling .Experience with Machine Learning algorithms (Regression, Classification, Clustering, PCA, etc.).Familiarity with Deep Learning frameworks – TensorFlow, Keras, PyTorch (preferred).Exposure to NLP , Computer Vision , and Generative AI is a plus.Hands-on with SQL, Power BI / Tableau for visualization.Familiarity with Jupyter Notebook, Git, and cloud ML environments .Excellent communication and presentation skills.Passion for teaching, mentoring, and simplifying complex topics.🎓 Qualification
Bachelor’s or Master’s Degree in Computer Science / Data Science / AI / Statistics / Mathematics / Engineering .Professional certifications (e.g., IBM Data Science, Google ML, AWS ML, or Coursera Specializations) are a plus.