A Trainer in the quality assurance and data processing domain plays a crucial role in ensuring that team members are equipped with the knowledge and skills necessary to maintain high standards in transaction monitoring and data labeling. The Trainer must stay updated with the latest industry standards and incorporate best practices into the training modules to enhance the team's capabilities. The Trainer is responsible for evaluating the training's effectiveness and making necessary adjustments to improve learning outcomes and operational efficiency. This role is pivotal in maintaining the quality and reliability of data, thereby ensuring that machine learning models perform their tasks accurately in real-world applications.

• Education and Skills:-
• Graduate/Post-graduate in relevant field.
• Min 2-3 years of process trainer or relevant experience.
• Professional & committed to work.
• Complete knowledge of the training domain in the Data Annotation field.
• Good knowledge of Data Labelling & Data Annotation.
• Should have good knowledge regarding all sorts of training tools, methodology/feedback delivery/BQM/TNI & etc.
• Should know Data Annotation/AI/ML/Data Processing/Data Labelling.
• Well Versed with 2D/3D photos & panoramas AI & Annotation Tools.
• Able to understand the instructions & able to convey the same to users.
• Job Description : - (Role & responsibilities)
• Create comprehensive training materials covering transaction monitoring, data processing, and quality assurance.
• Conduct regular training sessions for new hires and ongoing training for existing team members.
• Educate team members on the importance of accurate data labeling and its impact on machine learning model performance.
• Provide detailed guidelines and hands-on training to ensure high labeling accuracy.
• Stay informed about the latest developments in data processing and quality assurance.
• Revise training materials to incorporate new standards, technologies, and best practices.
• Assess the effectiveness of training programs through feedback, assessments, and performance metrics.
• Make necessary improvements to training approaches and materials based on evaluation results.
• Foster a culture of continuous learning and improvement within the team.
• Collaborate with quality analysts and other stakeholders to identify training needs and address skill gaps.
• Maintain detailed records of training sessions, participant progress, and feedback.
• Report on training outcomes and suggest actionable insights for improving quality assurance processes.