at Philips
Full TimeWe are seeking an experienced Data & AI Scientist with expertise in AI/ML to develop and deploy ML models, build end-to-end data pipelines, and implement MLOps practices. The candidate should have a strong background in translating business challenges into technical problems and identify the best ML models, statistical techniques, or AI approaches to solve them. Additionally, expertise in service innovation and predictive maintenance—leveraging AI/ML to optimize operations and predict equipment failures—is highly valued.
Your role:
Translate business challenges into technical problems and identify the best ML models, statistical techniques, or AI approaches to solve them.
Design, develop, and deploy end-to-end ML models, from data collection to production deployment.
Utilize data from connected devices and enterprise systems to address technical challenges and develop AI models for predictive maintenance.
Collaborate with cross-functional teams, including data engineers, software developers, and business stakeholders, to drive data-driven decision-making.
Research and stay up to date with the latest AI and ML technologies, including generative AI and agentic AI.
Contribute to continuous improvement by identifying new opportunities for innovation.
You are the right fit if:
You are already living in The Netherlands
You hold a Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, AI, or a related field.
You have at least 5 years of experience in data and AI scientist roles in an enterprise environment if you have a Master degree and 2-3 years if you have a Ph.D. Degree.
You are proficient in Python, R, SQL, and Spark for data science and engineering, with hands-on experience in relevant Python libraries (e.g., Scikit-learn, TensorFlow, PyTorch).
You have a deep understanding of model deployment, inference optimization, and real-time ML pipelines.
You have experience in data engineering, including building scalable data pipelines, ETL processes, and working with big data technologies.
You have strong knowledge of MLOps tools such as MLflow, Kubeflow, Airflow, and Docker/Kubernetes.
You have experience working with cloud platforms (AWS, Azure).
You are familiar with LLMs, generative AI, and agent-based analytics approaches.
Experience in service innovation and predictive maintenance is a strong plus.
You have strong interpersonal skills to work effectively within a team and communicate technical solutions to non-technical stakeholders.
You are flexible and open to learning new domains and technologies.
How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week. Onsite roles require full-time presence in the company’s facilities. Field roles are most effectively done outside of the company’s main facilities, generally at the customers’ or suppliers’ locations.
This role is an office role.
About Philips
We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.
Learn more about our business here.
Discover our rich and exciting history here.
Learn more about our purpose here.
If you're interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.
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