Marketing Data Science - General Manager

Job Responsibilities:
Analyzes and synthesizes complex data sets to develop innovative solutions, formulate advanced hypotheses, and create sophisticated proof of concepts to validate and enhance analytical models. Ensures the integrity and reliability of data through the implementation of robust validation protocols, advanced data governance frameworks, and comprehensive quality assurance processes, working under limited supervision. Participates in large-scale data mining projects, utilizing cutting-edge algorithms, AI, and machine learning techniques to uncover deep insights and actionable intelligence from vast, multi-source data sets. Coordinates the end-to-end deployment and rigorous validation of data science solutions, ensuring optimal performance, seamless integration, and alignment with enterprise systems and business processes. Builds and optimizes scalable, high-performance data pipelines and workflows using state-of-the-art big data technologies, ensuring efficient handling and processing of large-scale data for advanced analytics. Develops, documents, and disseminates advanced analytical methodologies and best practices, ensuring reproducibility, transparency, and fostering cross-functional collaboration and knowledge sharing. Evaluates and implements cutting-edge AI and machine learning techniques, pioneering innovative approaches to address complex business challenges and drive strategic advancements in analytics. Monitors, maintains, and continuously enhances the performance of deployed models, conducting regular reviews, updates, and optimizations to ensure sustained accuracy, relevance, and business impact. Identifies, assesses, and leads the implementation of advanced data science methodologies and technologies, driving continuous innovation and elevating Philips analytics capabilities to new heights. Guides junior data scientists and analysts, providing expert advice, training, and fostering a culture of excellence, continuous learning, and professional growth within the data science team. Participates in strategic initiatives to evaluate and integrate emerging technologies, open-source tools, and advanced data science frameworks, ensuring Philips stays at the forefront of innovation and maintains a competitive edge in the analytics domain.

Minimum required Education:
Bachelors / Masters Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
Minimum required Experience:
Minimum 15 years of experience with Bachelors OR Minimum 13 years of experience with Masters in areas such as Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition or equivalent.

Preferred Skills:
Data Analysis & Interpretation Data Governance Statistical Methods Statistical Programming Software Business Intelligence Tools Data Mining Machine Learning Engineering Fundamentals Research & Analysis Requirements Analysis Root Cause Analysis (RCA) Data Quality Management Systems Regulatory Compliance 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. Indicate if this role is an office/field/onsite role. 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 culture of impact with care here .