Principal Data Scientist, Supply Chain

- 10+ years of experience in data science, analytics, or programming, combining both industry and academic backgrounds - Bachelors degree in a technical discipline such as Operations Research, Computer Science, Statistics, Applied Mathematics, Economics, Engineering, or related quantitative/STEM majors (or equivalent work experience); Masters degree and/or PhD preferred - Proven expertise in time series forecasting - In-depth understanding of statistical methods and advanced modeling techniques (e.g., SVM, Random Forest, Bayesian inference, graph models, NLP, Computer Vision, neural networks, etc.) along with optimization and operations research methods - Demonstrated ability to address issues across the complete data stack, from data wrangling (using SQL or other methods) to stakeholder consumption at scale - Comprehensive knowledge of machine learning and data science best practices - Proficient in statistical programming (SAS, R, MATLAB) - Strong capability to convey technical concepts to non-technical stakeholders - Experience in object-oriented programming (Python, Java, C#, VBA, etc.) - Solid understanding of essential statistical concepts: linear regression, A/B testing, outlier analysis, probability distributions, tests for independence, etc. - Excellent teamwork and communication skills (verbal and written) - Familiarity with relational databases (e.g., MS SQL Server, Snowflake, Oracle) - Knowledge of cloud computing platforms is advantageous (e.g., Azure, AWS, Google Cloud, Databricks) - Skilled in utilizing Excel for financial modeling and reporting - Previous experience in data mining using enterprise systems (SAP or JD Edwards preferred) - Understanding of data warehousing and ETL best practices is a plus