DataScience Faculty

Role Overview

Data Science Faculty / Trainer

delivering end-to-end learning programs in Data Science, Machine Learning, AI, and Generative AI

hands-on practitioner and an educator

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.