INTERNSHIP DETAILS

Intern Data Scientist

CompanyPhilips
LocationTaipei
Work ModeOn Site
PostedSeptember 28, 2026
Internship Information
Core Responsibilities
The intern will collaborate on AI DevOps activities, including model deployment, monitoring, and data processing to ensure system integrity. They will also participate in technical discussions, statistical analysis, and model fine-tuning to optimize AI performance.
Internship Type
part time
Company Size
74108
Visa Sponsorship
No
Language
English
Working Hours
40 hours
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About The Company
Over the past decade we have transformed into a focused leader in health technology. At Philips, our purpose is to improve people’s health and well-being through meaningful innovation. We aim to improve 2.5 billion lives per year by 2030, including 400 million in underserved communities. We see healthcare as a connected whole. Helping people to live healthily and prevent disease. Giving clinicians the tools they need to make a precision diagnosis and deliver personalized treatment. Aiding the patient's recovery at home in the community. All supported by a seamless flow of data. As a technology company, we – and our brand licensees – innovate for people with one consistent belief: there’s always a way to make life better. Visit our website: http://www.philips.com/ Follow our social media house rules https://www.philips.com/a-w/about-philips/social-media.html
About the Role

Job Title

Intern Data Scientist

Job Description

Job Responsibilities:
• Collaborates extensively on AI DevOps activities, leveraging multiple tool sets at the solution level to streamline development, testing, inference, deployment, and monitoring processes with moderate complexity.
• Participates in discussions related to technical requirements, designs, and quality standards, providing inputs to ensure the robustness, scalability, and maintainability of AI solutions, working under direct supervision.
• Integrates deployable versions of machine learning models developed by data scientists into end products, ensuring compatibility, performance, and reliability of all system components.
• Handles data processing activities, including data cleansing, validation, and verification, to ensure the integrity and quality of data used for analysis and model training, with a focus on continuous improvement.
• Trains and retrains AI systems as necessary to adapt to changing data distributions, business requirements, and performance objectives, optimizing model performance through iterative refinement.
• Performs statistical analysis and fine-tuning of AI models using test results, hypothesis testing, and validation techniques to validate model assumptions, identify areas for improvement, and optimize model parameters.
• Contributes to activities within the on-site engineer team, providing the whole deployment plan and pipelines.
• Participates in the AI development process, working in pairing mode with equal team members, and actively contributing to requirements gathering, design discussions, code reviews, and quality assurance activities.
• Interacts with business, market, and IT stakeholders to formulate clear and actionable requirements for AI solutions, ensuring alignment with business goals, user needs, and technical capabilities.
• Ensures the quality of data and AI solutions developed, conducting thorough testing, validation, and verification activities to identify and address defects, errors, and performance issues before deployment.


Minimum required Education:
Master or PHD candidate in Biomedical Engineer, Computer Science, Information Management, Data Science, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.


Minimum required Experience:
Experience with Data processing, Data Analytics, AI Modeling or equivalent.


Preferred Experience:
Experience in using programming languages such as Python, R, JAVA, C/C++

Preferred Certification:
Artificial Intelligence Board of America (ARTiBA) certified


Preferred Skills:
• Troubleshooting
• Data Analytics
• Statistical Methods
• Data Harmonization & Processing
• Artificial Intelligence (AI)
• Scripting & Automation
• AI Algorithm Development
• DevOps
• Data Governance
• LLM deployment

Key Skills
Data ProcessingData AnalyticsAI ModelingPythonRJavaC/C++Statistical MethodsData HarmonizationArtificial IntelligenceScriptingAutomationAI Algorithm DevelopmentDevOpsData GovernanceLLM Deployment
Categories
Data & AnalyticsTechnologySoftwareScience & ResearchEngineering