Data Science & Data Analytics Trainer

Bits and Bytes Automation is looking for an experienced and skilled Data Science & Data Analytics Trainer who can teach complete Data Science and Data Analytics courses to students and working professionals.

The candidate should have strong practical and theoretical knowledge of Data Science, Data Analytics, and related technologies. The trainer must be capable of explaining complex concepts in a simple and practical way.

Key Responsibilities:

• Teach complete Data Science and Data Analytics courses from Basic to Advanced Level.
• Provide practical training with real-world projects and case studies.
• Teach Python, SQL, Statistics, and Data Analysis.
• Cover Machine Learning fundamentals and advanced concepts.
• Train students in Power BI, Tableau, Excel, and data visualization.
• Explain data cleaning, data preprocessing, data modelling, and exploratory data analysis.
• Guide students through live projects and industry-based assignments.
• Prepare students for interviews and industry-level requirements.
• Provide hands-on training and doubt-clearing sessions.

Required Skills:

• Complete knowledge of Data Science & Data Analytics.
• Strong command of Python and SQL.
• Knowledge of Machine Learning and Statistics.
• Hands-on experience with Power BI and Tableau.
• Knowledge of Excel, Data Visualization, and Data Modelling.
• Excellent communication and teaching skills.
• Ability to handle classroom and online training sessions.

Experience & Qualifications:

• 4–6 years of relevant experience in Data Science, Data Analytics, or professional training.
• Must be capable of teaching the complete Data Science & Data Analytics curriculum independently.
• Previous teaching or corporate training experience will be preferred.

Pay: ₹20,000.00 - ₹30,000.00 per month

Application Question(s):

• How many years of experience do you have in Data Analytics?
• ow much experience do you have in Data Science?

Experience:

• Data science: 4 years (Preferred)
• Data analytics: 5 years (Preferred)

Work Location: In person