We seek an experienced Data Scientist to join our Supply Chain Analytics team, developing Machine Learning models to forecast demand, optimize inventory, and reduce costs across our educational product portfolio. This role will drive data science best practices and introduce advanced analytics capabilities to support strategic supply chain decisions affecting tens-of-thousands of ISBNs and hundreds of millions in revenue every year. To accomplish this, the Data Scientist will work with a cross functional scrum team of Analytics Engineers and Data Analysts to build state of the art data products. This Data Science role will report to our Data Science manager who leads Data Science for Amplify's Sales, Marketing and Finance departments. As such, they will be empowered to innovate and participate in important decisions across the entire data stack. Essential Responsibilities: • Train, test, and deploy Machine Learning models: Drive the development of new Machine Learning capabilities by contributing at every stage of the Machine Learning delivery pipeline including research, evaluation, deployment and monitoring. • Seek the why behind every observation: Use advanced data analysis techniques to construct compelling narratives and recommend actions and strategies that our Supply Chain team can make to improve operations. • Work cross functionally to deliver superior data products: Contribute to development efforts from data ingestion, to data transformation, through to data analysis and machine learning in order to deliver high quality, impactful data products. • Give back to the broader Data Science team: Help our Data Science team continuously improve by leading team learning sessions and proposing novel tooling or architectures. Required Qualifications: • 2+ years of experience in a data science role working on Supply Chain forecasting or logistics optimization problems. • Proficiency with statistical methods and especially time series forecasting methodologies (eg. SARIMA, prophet, xGBoost) • Expert user of Python for data analysis tasks (data cleaning, manipulation, analysis). • Expert user of SQL, especially its use in data analysis tasks. • Experience training and evaluating the performance of machine learning models leveraging industry standard libraries like PyTorch, scikit-learn, tidymodels, xGBoost. • Experience deploying machine learning models from research environments into production environments like AWS Sagemaker, Databricks or Snowpark ML. • Demonstrated application of software development methodology and protocols, including using git for version control and testing. • Excellent communication skills in writing and conversation, especially with non-technical partners. • Experience driving self-directed projects and working cross-functionally. Preferred Qualifications: • Experience working with Snowflake. • Experience with container technologies, e.g. Docker and Kubernetes. • Background in education or in edtech.