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Supply Chain Data Scientist

PublishedPublished: 6/14/2022
Technology
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Job Description

Job Description

12 Months contract

Work schedule - Monday - Friday 8am -5pm PST


The essential requirements of the job include:

  • Bachelor’s degree in computer science, Computer Engineering, Data Science, Statistics or relevant technical field with 5+ years of related work experience OR Master’s degree in field with 3+ years of related work experience OR Doctoral degree in field with 0-2 years of work experience.
  • Strong hands-on proficiency in Python and SQL, with solid expertise in machine learning and deep learning.
  • Experience with ETL and data engineering, statistics, time-series forecasting, feature engineering, hyperparameter optimization, and model validation.
  • Ability to communicate analytical results clearly to both technical and non-technical audiences, and to continuously improve solutions based on feedback.
  • It would be a plus if you also possess previous experience in Supply chain optimization – inventory, transportation, sourcing, distribution, fulfillment, planning, etc.
  • Writing high-performance code and deploying algorithms in a production environment. Building AI pipelines for operational use
  • Overview
  • The Senior Supply Chain Data Scientist is responsible for building and optimizing machine learning and statistical models that improve demand predictability, inventory decisions, and supply chain responsiveness.
  • This position requires strong modeling and coding skills, and the ability to translate complex data into clear business insights that drive impact.
  • Develop and optimize machine learning and statistical models, including time-series forecasting and hyperparameter optimization, to improve demand forecast accuracy for operational use.
  • Build robust data and ETL pipelines, develop data visualizations, and automate model training, deployment, and monitoring using MLOps practices to deliver reliable, scalable forecasts and actionable supply chain insights.
  • Collaborate with business stakeholders to understand their challenges and translate complex analytical results into actionable recommendations.
  • Understand supply chain processes and build AI agent pipelines to automate routine workflows and support faster, more effective decision-making.
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