Greater Istanbul
I am an experienced data science lead with a solid software development background. I have developed projects and participated in publications mostly related to; customer analytics, recommendation systems & natural language processing. The publications can be reached at; https://www.researchgate.net/profile/Ahmet_Tugrul_Bayrak2/publications
• Defining long-term roadmaps to align innovation with corporate business goals • Leading R&D lifecycle for diverse projects • Managing R&D budgets, resource allocation, and end-to-end project tracking • Presenting strategic insights and R&D progress to senior management • Driving continuous learning and staying ahead of emerging AI trends
• Leading and managing a team of data scientists • Developing the data science strategy and roadmap • Collaborating with cross-functional teams to deliver data-driven solutions • Ensuring the quality and accuracy of data science work • Communicating data science results and insights to senior management and stakeholders
• Delivering the course "Applied LLMs", focusing on practical applications of Large Language Models • Sharing practical industry knowledge and real-world applications of AI, data science, and emerging technologies • Guiding students in bridging the gap between theoretical foundations and industry practices • Supporting academic training with case studies, hands-on projects, and professional insights
• Serving on the advisory board of the Computer Engineering Department • Provideingindustry insights to support curriculum development and modernization • Advising on emerging technologies and skills required in the tech sector • Contributing to bridging the gap between academic training and industry expectations
• Designing and implementing search and ranking models in multiple languages for the Huawei app gallery • Creating and refining the features used in the models to improve search and ranking results • Conducting A/B testing to evaluate the success of the models and make data-driven improvements • Keeping up-to-date with the latest trends and advancements in search & ranking algorithms and integrating new technologies and techniques into existing models
• Market basket generation by genetic algorithm • Customer & employee churn analysis using RNN with personalized sequential data • Building a recommendation system for online fast-food customers via a hybrid collaborative filtering approach • Sales prediction for fast-food branches
• Mapping hotel entities coming from different providers based on their similarities • Detecting & merging near-duplicate customer records by machine learning • Customer churn analysis using sequential data • Creating a topic and sentiment classification system for customer reviews • Creating a spell correction system that uses a custom FastText model and similarity distances for the tourism domain