Data Scientist (all genders welcome)

• Translate business and product goals into well-defined data science and machine learning problems, identifying where data-driven approaches can generate the most value
• Conduct rigorous data analysis and experimentation, identifying patterns, quantifying uncertainty, and adapting strategies based on findings
• Design, develop, and validate machine learning models and analytical workflows, advancing solutions from research to production
• Define success metrics and key performance indicators in collaboration with stakeholders, ensuring solutions deliver measurable business impact
• Produce clear documentation, visualisations, reports, and dashboards for both technical and non-technical audiences
• Validate data quality, recommend improvements to data collection processes, and identify risks including model bias, drift, and fairness concerns.
• Stay current with advances in statistical and machine learning methods, tools, and industry best practices, assessing their applicability to our goals.

Do you have experience in Torch?, To become part of the Rosenxt family, you have creative, self-reliant, collaborative skills and want to help the team do its best work. Moreover you should bring with you:

• Proven experience designing experiments, building models, and delivering data science solutions in production
• Solid understanding of supervised and unsupervised learning algorithms, statistics, and linear algebra
• Hands-on experience applying ML and statistical methods to complex real-world data (e.g. sensor data, time series, signal recordings)
• Strong proficiency with Python and core data science libraries (e.g. PyTorch, scikit-learn, pandas, numpy), or strong experience in other languages and a willingness to learn Python
• Practical skills in statistical analysis, data visualisation, and feature engineering
• Clear and comprehensive documentation of code, methods, and experiments
• Experience with Git, environment management (e.g. Docker, poetry, uv), and at least one major cloud platform (AWS, Azure, or GCP)
• Ability to implement algorithms from academic papers
• Experience processing ultrasound data & video data
• Experience with PyTorch, Py Torch Lightning, Open CV, CVAT, Docker, ROS