Applied Scientist (ML/AI)

(Toegepast Wetenschapper (ML/AI)) An Applied Scientist (ML/AI) forms an essential player in teams focused on developing and implementing innovative solutions within sectors. This professional works on challenging research projects where advanced algorithms for machine learning and artificial intelligence are developed and optimized. The work involves analyzing complex datasets, creating predictive models and translating these insights into practical applications that help clients solve strategic issues. Together with a multidisciplinary team of data scientists, software developers and analysts, project progress is discussed and recommendations for improvements are made. The work takes place in a stimulating and collaborative environment where knowledge sharing and innovation are central. Modern offices are equipped with advanced technologies and there is an open culture where every voice is heard. Additionally, there is often the possibility to work partially remotely. The role offers the chance to be at the forefront of technological advancement. Applied Scientists have the freedom to be creative, conduct experiments and bring ideas to life. Moreover, they get the opportunity to collaborate with leading experts in the field and contribute to the development of groundbreaking products that impact the market. The work has direct impact on the efficiency and effectiveness of business processes and financial services. Through skills in ML and AI, clients can make better decisions, optimize their operations and create value for their end users. Applied Scientists help organizations leverage opportunities they might otherwise overlook. Among the challenges is staying up to date with the latest trends and innovations in this dynamic sector, and applying these within tight deadlines. Additionally, the complexity of data and required analyses demands that problem-solving skills are continuously sharpened. For this position, typically a WO education in Computer Science, Artificial Intelligence, Data Science, Mathematics or a related technical field is required, often supplemented with a Master's or PhD. Experience with machine learning frameworks (such as TensorFlow, PyTorch), programming (Python, R) and statistics are essential competencies. Knowledge of deep learning, natural language processing and cloud platforms are valuable skills. Career opportunities consist of advancement to senior scientist, research lead, principal scientist or specialization in specific AI areas such as computer vision, NLP or reinforcement learning.