Data Science, ML & Blockchain Trainer

Company Description

VocSkill is an ed-tech platform founded by IIT alumni and renowned educationalists, certified by the National Skill Development Corporation. Our mission is to empower learners by creating an ecosystem that makes them job-ready. We offer industry-relevant courses curated by professionals to meet market needs, with a proven track record of successful training and skill development. Our certificate programs include E-Commerce, Business Analytics, Digital Marketing, Fintech & Blockchain, HR Analytics, Corporate Banking, and Design Thinking.

Role Description

Data Science, ML, Blockchain & Data Analytics Trainer

You will be responsible for:

• Delivering engaging lab sessions covering supervised/unsupervised ML algorithms, neural networks, ensemble methods, blockchain fundamentals, smart contracts, and consensus algorithms.
• Teaching data warehousing concepts including OLAP operations, dimensional modelling, and data preprocessing.
• Guiding students in implementing classification, clustering, association rule mining, and web mining algorithms using tools like Python, R, and WEKA.
• Designing assignments, projects, and assessments that align with university syllabus and industry standards.
• Mentoring students towards applying concepts in real-world applications and industry projects.
• Staying updated on emerging trends in Data Science, Blockchain, and Data Analytics.

Qualifications

• Strong knowledge in

  Machine Learning, Blockchain, Data Warehousing, and Data Mining

  .
• Proficiency in

  Python, R, SQL

  , and relevant ML/Blockchain tools (TensorFlow, PyTorch, Scikit-Learn, Solidity, etc.).
• Familiarity with

  dimensional modelling, OLAP operations, classification, clustering, association rule mining

  .
• Hands-on experience with

  smart contract development

  and blockchain frameworks.
• Excellent teaching, communication, and mentoring skills.
• Minimum Bachelor’s/Master’s degree in Computer Science, Data Science, Engineering, or related fields.
• Prior teaching/training experience in academic or corporate settings preferred.