DataScience Faculty

# ; 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.