Dinu Scripnic

- Join the sports data team working to create products combining sports and betting data – inside a department that is a key focus for Sportradar’s future growth. - Work with a range of different languages and components that use Golang and Python on top of multiple cloud-based AWS serverless architecture. - Develop Machine Learning and Artificial Intelligence solutions that can improve data analysis and decision-making processes within Sportradar's operation

• Developed and maintained a robust full-stack application for collecting, analyzing, and controlling key performance indicators (KPIs) for 10+ company departments. • Orchestrated and managed data workflows using Prefect for seamless coordination within a distributed environment. • Utilized Docker for efficient redeployment, enhancing system efficiency and scalability. • Automated setup scripts and standardized configurations, resulting in a 75% reduction in company-wide setup time

• Implemented RESTful APIs with Django, enhancing system functionality and efficiency. • Enhanced Natural Language Processing (NLP) model performance by 50% and aligned with updated requirements. • Engineered a responsive React frontend for enhanced user experience and cross-device compatibility. • Multi-tasked across multiple roles to boost performance, generate results and meet deadlines and expectations. • Demonstrated the product to several stakeholders, including the management board of the University.

Summa cum Laude 3-year Bachelor program with focus on: Full-stack development, Data Science, AI and Machine Learning Thesis Topic: Data-Driven Study Program Monitoring, Dynamic Topic Modeling Elective: Bio-Informatics