Data Scientist (Supply Chain)

The Applied Research team addresses hard, novel challenges that arise in product development or customer engagements. As a Data Scientist, Supply Chain, you'll bring your knowledge and proven data science expertise to conduct research in machine learning-based solutions that improve our products and help our customers. Qualified candidates are deeply analytical with a keen understanding of artificial intelligence, machine learning, and data science. They are experienced researchers who know how to design worthwhile experiments and empirically derive conclusions. They have the ability, inclination, and experience to conduct research that solves practical problems. They have the communication skills to work closely with both research colleagues and customers.

You will:

• Independently and effectively engage with internal product developers, external customers, and subject matter experts to understand and solve critical technical challenges through the application of cutting-edge artificial intelligence
• Conduct research and create models for commercial and industrial applications in: forecasting stochastic demand, economics based inventory optimization, manufacturing and network planning, transportation routing and resource scheduling, anomaly detection, prescriptive maintenance (e.g. based on IOT data), health and safety (e.g. based on computer vision and IOT data).
• Conduct research across artificial intelligence areas including reinforcement learning, foundation models, graph neural networks, causal modeling, transferability and continuous learning
• Pioneer procedures and/or automated toolsets to more efficiently and effectively perform data science activities
• Contribute to AI product development and key data science research areas, internally and externally
• Propose new projects or initiatives that will yield business benefits and evaluate project plans and proposals
• Evaluate and respond to RFPs related to artificial intelligence
• Conduct research and write patent applications and technical publications

You’ll Have:

• Experience with research-level innovation in Data Science and ML, preferably with an advanced degree.
• 5+ years of experience in one or more of forecasting, optimisation (inventory/ supply chain/ network/ transportation), procurement, prescriptive maintenance, fine-tuning language models, creating domain agents, computer vision. Experience with reinforcement learning including MARL, graph neural networks, economic and probabilistic modeling is a plus. 
• Strong understanding of Data Science, including machine learning, statistics, probability, and modeling.
• Significant experience with Data Science programming languages, such as Python, R, Matlab
• Significant experience with machine learning frameworks, such as PyTorch, TensorFlow, Theano, and Keras.
• Applied knowledge of ML techniques/algorithms including linear models, neural networks, decision trees, Bayesian techniques, clustering, and anomaly detection
• Significant experience managing large volumes of data (terabytes or more)
• Experience with leading project teams, specifically data science teams
• Strong written and verbal communications, ability to translate complex technical topics to internal and external stakeholders.