Data Scientist

Company Description Rayio develops software for radiology applications that enables disease detection, segmentation, and treatment planning with the objective to support radiologists by assisting in the identification of diseases and helping medical teams make the most appropriate treatment decisions.

Raiyo Inc is the spin out of the Healthcare department of Robovision.

Role Description As a Data Scientist at Robovision, you will work full time in a hybrid setup based in Aalst, with the possibility to work from home part of the week (Initially fully remote). You will collaborate with the team to design, build, and validate data-driven solutions that enhance industrial vision intelligence and support outcome assurance for customers. Typical responsibilities include collecting and preprocessing data from various sources, performing exploratory data analysis, building statistical and machine learning models, and evaluating their performance in production environments. You will create clear visualizations and reports for internal stakeholders and clients, support continuous model improvement as production conditions evolve, and contribute to best practices for data quality, governance, and documentation. You will also help integrate models into scalable systems, collaborate with engineers on deployment, and participate in knowledge sharing across the organization. You will be also the owner of product risk analysis and drive related process..

Main accoutabilities:

• Collect and analyze data related to medical devices, including patient data, device data, and other relevant information
• Develop AI models, selecting appropriate algorithms, designing training and validation datasets, and optimizing model performance
• Ensure accuracy and reliability to improve medical device performance and patient outcomes
• Collaborate in cross-functional teams with other stakeholders such as software development engineers, regulatory specialists, medical specialists
• Ensure that patient data is handled in a responsible and ethical manner
• Ensure appropriate management of the rsika analysis of each product
• Collaborates with colleagues in other teams and groups to achieve the overall aligned business or company goals
• Provide, together with other team members, realistic estimates regarding efforts required to develop models
• Contribute, as appropriate, to the software related records as part of the Medical Device File

Education:

• Master's or PhD’s degree in Computer Science, Data Science, or a related field

Experience:

• Minimum of 3 years of experience in data science, either gathered through education, personal or professional projects.
• Preferably, professional experience in data science for medical devices, including experience with regulatory compliance.

Competencies:

• Proficiency in programming languages and data manipulation tools, such as Python, SQL, Pandas, SciPy, OpenCV, and Pytorch to develop algorithms and perform data analysis
• Capacity to understand a problem and creativity to conceive approaches that lead to high performance solutions.
• Good understanding of regulatory requirements, such as 21CFR Part 820, EN ISO 13485, IEC 62304 and other applicable standards
• Basic understanding of the software development lifecycle, including requirements gathering, design, development, testing, and maintenance.
• Familiarity with machine learning algorithms, deep learning, and statistical models to build predictive models and analyze complex data sets
• Experience with data visualization tools such as Matplotlib, to create visual representations of complex data sets to facilitate insights and decision-making
• Knowledge of data cleaning and preprocessing techniques, including feature engineering, dimensionality reduction, and data normalization
• Good understanding of model deployment and API software interfaces
• Strong understanding of mathematical and statistical concepts, such as probability, linear algebra, and hypothesis testing, to perform data analysis and model validation
• Ability to identify and select appropriate data models and evaluation metrics based on the specific problem and domain
• Excellent problem-solving skills, with the ability to identify and resolve issues and bugs in data and models
• Experience with data integration and data engineering, including data quality assessment and data profiling
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