Senior Data Scientist – Supply Chain Optimization

Job Title: Senior Data Scientist Supply Chain Optimization

Location: Deerfield FL (Hybrid 3 Days Onsite)

Duration: 6-Month Contract-to-Hire

W2 Contract

Seeking a Senior Data Scientist with strong expertise in Supply Chain Management Machine Learning and AI deployment. The ideal candidate will have recent experience deploying AI/ML solutions into production delivering measurable business impact and driving data science initiatives focused on demand forecasting inventory optimization logistics planning and supply chain analytics.

• 5 years of experience as a Data Scientist with a strong focus on Supply Chain optimization.

• Recent experience (within the last 3 years) deploying AI/ML solutions at scale with measurable business outcomes.

• Proven experience productionizing machine learning models (MLOps) not just building prototypes.

• Hands-on expertise in Python SQL and Jupyter Notebooks.

• Strong background in:

  • Demand Forecasting

  • Inventory Optimization

  • Logistics Optimization

  • Sales & Marketing Analytics

  • Supply Chain Modeling

• Experience building and deploying ML models in production environments.

• Recent experience with AI use cases such as RAG-based Chatbots or GenAI solutions that delivered business value.

• Ability to articulate ROI value realization scaling strategies and use-case prioritization frameworks.

• Experience working directly with business stakeholders to gather requirements prioritize initiatives and communicate outcomes.

• Experience working in early-stage or evolving data environments and helping shape data strategies.

• Microsoft Azure ecosystem experience:

  • Azure AI Foundry

  • Azure Machine Learning

  • Azure Synapse Analytics

  • Azure SQL Managed Instance

  • Microsoft Fabric

• Experience collaborating with architects and engineering teams to deploy scalable ML solutions.

• Strong understanding of MLOps model governance and production deployment best practices.

• Design develop and optimize machine learning models to solve supply chain challenges.

• Build AI/ML solutions for demand forecasting inventory management and logistics optimization.

• Deploy and scale machine learning models into production environments.

• Partner with business stakeholders to identify high-value use cases and quantify business impact.

• Develop frameworks for ROI measurement value capture and AI adoption.

• Work closely with architects and engineers to integrate ML solutions into enterprise systems.

• Drive end-user adoption of AI-enabled solutions through scalable production-ready implementations.