KG institute of engineering and technology
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The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
DA DS Trainer JD:
Key Responsibilities:
Develop and deliver comprehensive training programs on data science topics, including machine learning, artificial intelligence, big data, data mining, and predictive analytics.
Create engaging and interactive training materials, including presentations, hands-on exercises, case studies, and assessments.
Conduct classroom, online, and one-on-one training sessions for students at different skill levels.
Evaluate students' performance and progress, providing feedback and support to help them improve.
Stay up-to-date with the latest trends and best practices in data science and incorporate them into training programs.
Collaborate with other trainers and industry experts to continuously improve training content and methodologies.
Assist in the development of training schedules and manage training logistics.
Provide mentorship and career guidance to students aspiring to build a career in data science.
Qualifications:
Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field; a Master’s degree is a plus.
Proven experience as a Data Science Trainer or a similar role.
In-depth knowledge of data science concepts and hands-on experience with tools like Python, R, TensorFlow, and Hadoop.
Excellent presentation and communication skills.
Strong organizational and time-management abilities.
Ability to simplify complex concepts and deliver them in an understandable manner.
Certification in Data Science (e.g., Microsoft Certified: Azure Data Scientist Associate) is preferred.
Preferred Skills:
Experience with LMS (Learning Management Systems) and e-learning platforms.
Strong analytical and problem-solving skills.
Ability to adapt training methods to different learning styles.
Passion for continuous learning and professional development.
Benefits:
Competitive salary and performance-based incentives.
Professional development opportunities.
Flexible working hours.
Collaborative and innovative work environment.
Read less
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
DA DS Trainer JD:
Key Responsibilities:
Develop and deliver comprehensive training programs on data science topics, including machine learning, artificial intelligence, big data, data mining, and predictive analytics.
Create engaging and interactive training materials, including presentations, hands-on exercises, case studies, and assessments.
Conduct classroom, online, and one-on-one training sessions for students at different skill levels.
Evaluate students' performance and progress, providing feedback and support to help them improve.
Stay up-to-date with the latest trends and best practices in data science and incorporate them into training programs.
Collaborate with other trainers and industry experts to continuously improve training content and methodologies.
Assist in the development of training schedules and manage training logistics.
Provide mentorship and career guidance to students aspiring to build a career in data science.
Qualifications:
Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field; a Master’s degree is a plus.
Proven experience as a Data Science Trainer or a similar role.
In-depth knowledge of data science concepts and hands-on experience with tools like Python, R, TensorFlow, and Hadoop.
Excellent presentation and communication skills.
Strong organizational and time-management abilities.
Ability to simplify complex concepts and deliver them in an understandable manner.
Certification in Data Science (e.g., Microsoft Certified: Azure Data Scientist Associate) is preferred.
Preferred Skills:
Experience with LMS (Learning Management Systems) and e-learning platforms.
Strong analytical and problem-solving skills.
Ability to adapt training methods to different learning styles.
Passion for continuous learning and professional development.
Benefits:
Competitive salary and performance-based incentives.
Professional development opportunities.
Flexible working hours.
Collaborative and innovative work environment.
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