You will be taken to Philips’s own careers page to apply. Job ID 586470.
Job description
Job Title AI/ML Data Scientist - Sales Forecasting Job Description Job Responsibilities:
Demand Forecasting: Design, build, and deploy scalable demand forecasting models (time-series, ML-based) to predict product demand at SKU, category, channel, and regional levels.
Discount & Price Simulation: what-if simulation tools to optimize discount strategies and maximize margin.
End-to-End Model Ownership: Own the full ML lifecycle—data exploration, feature engineering, model training, validation, deployment, monitoring, and iteration.
•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.
Minimum required Education: Bachelor's / Master's Degree in Computer Science, Econometrics, Artificial Intelligence, Applied Mathematics, Statistics or equivalent.
Minimum required Experience: Minimum 6 years of experience with Bachelor's 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.
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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.
