Data Scientist

Job Title

Data Scientist

The Data Scientist is responsible for ensuring data quality, accuracy, and reliability through rigorous validation and cleansing techniques, driving comprehensive quality control measures, working under limited supervision. The role utilizes advanced algorithms and AI, participates in end-to-end data mining projects to extract deep insights from complex data sources. The role deploys and tests data science solutions rigorously, ensuring optimal performance and seamless integration with enterprise systems. The role maintains robust data pipelines and workflows and leverages big data technologies to support advanced analytics projects.

Your role:

The Patient Safety & Quality Data Scientist applies advanced statistical and machine learning techniques to extract insights from complex datasets, supporting strategic decisions and operational efficiency. The role develops predictive models, creates visualizations using tools such as Python, R, and Palentir, and ensures data accuracy through robust storage and cleansing processes. It also maintains compliance with global data privacy standards (e.g., GDPR, HIPAA) through strong governance and security practices.

• Analyzes multifaceted and high-dimensional data problems, developing innovative solutions, formulating sophisticated hypotheses, and creating advanced proof of concepts to validate and refine analytical models.
• Ensures the highest standards of data quality, accuracy, and reliability by designing and implementing rigorous validation protocols, advanced data cleansing techniques, and comprehensive quality control measures, working under limited supervision.
• Participates in end-to-end data mining projects, utilizing advanced algorithms, machine learning models, and AI techniques to extract deep and actionable insights from complex, large-scale data sources.
• Executes the deployment and rigorous testing of data science solutions and insights, ensuring optimal performance, scalability, and seamless integration with existing enterprise systems and workflows.
• Maintains robust, scalable data pipelines and workflows, leveraging cutting-edge big data technologies and database management systems to support advanced analytics and machine learning projects.
• Develops, documents, and disseminates comprehensive methodologies, processes, and analytical findings, ensuring transparency, reproducibility, and facilitating cross-functional knowledge sharing and collaboration.
• Evaluates and implements state-of-the-art machine learning and AI techniques, continuously researching and applying novel approaches to solve highly complex business problems and drive strategic innovation within Philips.
• Presents complex data-driven insights and strategic recommendations to senior stakeholders, effectively translating intricate analytical results into clear, actionable business strategies and influencing key decision-making processes.
• Monitors, maintains, and continuously improves the performance of deployed models, conducting regular reviews, updates, and optimizations to ensure sustained accuracy, relevance, and business impact.
Interacts and collaborates with cross-functional teams, including IT, data engineering, and various business units, to ensure the successful operationalization, integration, and scaling of data science solutions across the organization.

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You're the right fit if:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition or equivalent OR no prior experience required with Master's Degree.

• 6+ years of experience in data analysis, predictive modeling, and data strategy development

• Proficiency in programming languages such as SQL and Python

• Experience with data visualization and analytics tools such as Power BI, R, Databricks, and SAP MES , as well as complaint-management systems like TrackWise .

• Hands-on experience with statistical modeling , data mining techniques, unstructured data processing, AI/ML workflows , and large-language-model LLM-based architectures

• Strong analytical and problem-solving skills, with the ability to translate complex data into actionable insights and strategic recommendations

• Excellent documentation skills with the ability to clearly communicate complex technical concepts

• Excellent communication and interpersonal skills, with the ability to effectively collaborate with stakeholders at all levels of the organization

• Ability to work effectively in a fast-paced and dynamic environment

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-based role.

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