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.