Leadership and Team Management:• Led a team with daily goals and ensuring quality assurance.• Assigned tasks, established due dates, and tracked group performance.• Monitored team performance closely through observations and key metric tracking.• Identified and managed underachievers appropriately.• Encouraged teammates and cultivated an open culture of communication.Objective Setting and Workflow Coordination:• Oversaw daily activities coordinated workflow and defined team objectives.• Coordinated with teams in the Netherlands on workflow, recommendations, etc.Client Satisfaction and Data Delivery:• Successfully provided the client with data according to their needs.• Providing input to developers on client-delivered data for additional enhancements.Training and Guidance:• Determined the need for training and offering guidance to team members to improve productivity and reduce errors.Reporting and Documentation:• Generated Excel reports to track team performance and deliverables.

Clip Identification:• Identified clips ranging from five seconds to substantial pieces of content.• Determined usage details such as time, location, territory, and specific channel.Insights and Analysis:• Captured second-by-second insights into TV brand instances using automated logo recognition.• Utilized closed caption brand detection for additional insights.• Recognized a brand's logo throughout live videos and matches.Media Exposure and Frequency:• Identified media exposure, channel, and frequency by household.• Recognized the logo to analyze how well the program is performing.Data Analysis and Balance:• Maintained a balance between quantity and quality when analyzing program data.Project and Software Improvement:• Involved in providing input on running projects or software for continuous improvement.

• Examine Data Quality: Thoroughly check and double-check the input data to ensure its accuracy and reliability to ensure the effectiveness of the program.• Certification for Quality Control: Provided precise and accurate certification to establish quality control measures for the logo recognition system.• Balancing Quantity and Quality: Analyzed data within the program to strike a balance between the quantity of data and its quality, ensuring that the data is of the high quality required for training accurate machine learning models.• Bounding Box Creation: Bounded box creation on unprocessed photos which involves annotating the images with bounding boxes around the logos to provide the necessary training data for the model to learn and recognize logos accurately.