DataScience Faculty

Role Overview We are seeking aData Science Faculty / Trainerwith a proven blend ofindustry execution (IT or service-based projects)andacademic delivery (EdTech or corporate training) . You will be responsible fordelivering end-to-end learning programs in Data Science, Machine Learning, AI, and Generative AI , while also integratingreal-world IT project experienceinto your sessions. The ideal candidate is both ahands-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. Conducthands-on lab sessionsandcase 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 inPython, NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn . Strong knowledge ofStatistics, Probability, Linear Algebra, and Data Modeling . Experience withMachine Learning algorithms(Regression, Classification, Clustering, PCA, etc.). Familiarity withDeep Learning frameworks– TensorFlow, Keras, PyTorch (preferred). Exposure toNLP ,Computer Vision , andGenerative AIis a plus. Hands-on withSQL, Power BI / Tableaufor visualization. Familiarity withJupyter 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 inComputer Science / Data Science / AI / Statistics / Mathematics / Engineering . Professional certifications (e.g., IBM Data Science, Google ML, AWS ML, or Coursera Specializations) are a plus.