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 and deliver

  interactive sessions

  on

  Data Analytics concepts including Excel Analytics, SQL, Power BI, Tableau, Python (Pandas, NumPy), and Statistics.

• Conduct

  lectures, workshops, and lab sessions

  for students or professionals across beginner to advanced levels.
• Customize training content based on audience profiles — working professionals, graduates, or corporate teams.
• Facilitate

  hands-on exercises, real-time projects, and case studies

  to reinforce practical learning.
• Ensure high engagement through live problem-solving, Q&A, and feedback sessions.

Required Skills and Competencies

• Demonstrate expertise in tools such as

  Excel (Advanced), Power BI, Tableau, SQL, Python, and Google Data Studio.

• Teach core concepts:

  Descriptive & Predictive Analytics, Data Cleaning, Data Transformation, and Visualization.

• Incorporate real-time dashboards, KPI tracking, and report automation into training modules.
• Stay updated on

  emerging analytics tools and AI-driven data platforms

  to continuously enhance the curriculum.

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.