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Mid-level ML role, metro location, and known employer increase applicant competition.
Core ML skills are transferable, but supply-chain and operations-research requirements add domain specificity.
Explicit 3–6 years, supply-chain domain knowledge and mandatory ML/SQL toolset make filters stringent.
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Lead building and optimizing machine learning classifiers to support supply chain forecasting solutions.
Conduct and present data mining and ad-hoc analyses, addressing forecasting issues and data quality concerns.
Mentor junior team members and support client onboarding and ongoing use of Blue Yonder’s Luminate Planning and Applied Data Science offerings.
3 to 6 years of relevant experience in data science or related fields.
Proficiency in Python and at least one of: NumPy, Pandas, Matplotlib, Seaborn.
Strong understanding of machine learning algorithms (e.g., Linear Regression, K-Means Clustering, Naive Bayes).
Bachelor’s or Master’s degree in Computer Science with a focus on Data Science.
Experience working with supply chain concepts and statistical analysis within data science projects.
Comfortable with operations research methods such as integer, linear, and stochastic programming.
Skilled in data visualization (e.g., Streamlit, Power BI), SQL querying, and effective communication with cross-functional stakeholders.