Experienced Data & AI Scientist – Service Innovation & Predictive Maintenance

Job Title

Experienced Data & AI Scientist – Service Innovation & Predictive Maintenance

Job Description

We are looking for a seasoned and agile Data & AI Scientist to join our dynamic team of data science professionals. This role is ideal for someone passionate about designing, developing, and deploying end-to-end AI solutions that span the full lifecycle—from business understanding to production-grade deployment. You will bring strong expertise in machine learning, time series analysis, and generative AI, and use these skills across multidisciplinary domains, with a particular focus on predictive maintenance and service innovation —leveraging AI/ML to optimize operations and predict equipment failures.

You will be expected to operate with both depth and breadth—crafting robust AI/ML solutions, integrating MLOps best practices, and leveraging AI tools for enhanced productivity and agile solution development.

Your role

• Translate complex business problems into well-scoped data science use cases.

• Design, develop, and deploy ML models through the full lifecycle—data collection, exploration, modeling, validation, and production deployment.

• Leverage data from connected devices and enterprise systems to develop AI solutions for predictive maintenance and intelligent service innovation

• Leverage cloud-native solutions (e.g., Azure, AWS) for deployment, scalability, and automation.

• Incorporate generative AI and agentic AI approaches into practical use cases to drive innovation.

• Collaborate closely with cross-functional teams—data engineers, software engineers, product managers, and business leads.

• Continuously innovate, adopt new AI trends, and use AI tools daily (e.g., coding assistants, automation frameworks) to boost your personal and team productivity.

You are the right fit if:

• You hold a Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, AI, or a related field.

• You possess strong expertise in time series modeling, predictive analytics, and ML algorithms.

• You bring at least 5 years of hands-on experience with a Master’s degree, or a minimum of 3 years with a Ph.D., building and deploying AI/ML solutions in an enterprise environment.

• You are proficient in Python, R, SQL, Spark for data science and engineering, with hands-on experience in relevant Python libraries (e.g., Scikit-learn, TensorFlow, PyTorch).

• You have experience in data engineering, including building scalable data pipelines, ETL processes, and working with big data technologies.

• You have a deep understanding of model deployment, inference optimization, and real-time ML pipelines.

• You have strong knowledge of MLOps tools such as MLflow, Kubeflow, Airflow, and Docker/Kubernetes.

• Are skilled in designing and maintaining cloud-native solutions on platforms like Azure or AWS.

• You stay current with generative AI and agent-based approaches and know how to apply them in business contexts.

• You demonstrate experience or strong interest in predictive maintenance, service innovation, or IoT-driven AI use cases.

• You communicate effectively with both technical and non-technical stakeholders.

• You are highly agile, quick to adapt to change, and proactive in leveraging AI to maximize your productivity.

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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