Senior Data Scientist
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Saleconix, founded in 2005, specializes in smart IoT solutions with advanced customization services for electronic development and firmware design. The company focuses on delivering tailored, high-performance technologies for diverse industrial and commercial applications. Team members collaborate closely with clients to turn complex requirements into robust, scalable solutions. Saleconix values innovation, technical excellence, and practical problem-solving. Role Description
The Senior Data Scientist will play a key role in designing, developing, and deploying data-driven solutions that enhance Saleconix’s smart IoT products and services. Day-to-day responsibilities include exploring complex datasets, building statistical and machine learning models, developing analytical dashboards, and translating data findings into actionable recommendations for product and engineering teams. The role involves close collaboration with firmware and electronics engineers to integrate analytics into IoT platforms, as well as presenting insights to internal and external stakeholders in a clear, structured manner. This is a contract role. It is a hybrid position based in Ghent, with a combination of on-site work and some work-from-home flexibility. Qualifications Strong Data Science and Data Analytics skills, including experience with modeling, machine learning, and data-driven decision-making. Solid foundation in Statistics and Data Analysis for hypothesis testing, experiment design, and model validation. Proficiency in Data Visualization for building clear dashboards, reports, and visual narratives that communicate complex insights. Hands-on experience with common data science tools and languages (e.g., Python or R, SQL, and relevant libraries/frameworks). Experience working with IoT data, embedded systems, or sensor-based datasets is highly beneficial. Ability to work in a hybrid setup in Ghent, collaborating effectively with cross-functional teams. Strong problem-solving skills, attention to detail, and the ability to explain technical concepts to non-technical audiences. Master’s degree or PhD in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field, or equivalent practical experience.
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