• Reviewed customer data for risk identification, utilizing SQL queries to extract and analyze relevant information, identifying risks in over 100 datasets, and reducing potential incidents by 15%.• Developed interactive customer dashboards with Power BI, enhancing data accessibility and facilitating strategic decision-making for key stakeholders. 93% of clients used the dashboards, leading to a 30% improvement in decision-making speeds.• Collaborated with the R&D team to power machine learning models, utilizing Python for data preprocessing and model implementation, which improved model accuracy for identifying and tagging safety events by 35%.• Led a team of 6 members in a project aimed at enhancing data-driven decision-making within the organization, overseeing project milestones and ensuring successful project delivery.• Optimized data collection and reporting pipelines, improving data accuracy and reducing reporting time by 20% through automated processes.• Monitored and analyzed telematics data from ELDs to identify potential risks, such as driver fatigue or unsafe driving behaviors, reducing risk incidents by 10%.