AI/ML Data Scientist - Sales Forecasting

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Skills you'll use

What you'll do

• 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.

Who can apply

• Minimum 6 years of experience with Bachelor's in areas such as Data Analytics, Data Science, Data Mining, Artificial Intelligence, Pattern Recognition or equivalent.

About Philips

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