Hexion

Lead Data Scientist - US Remote

Hexion • $115K — $145K *
Columbus, OH 43230In-Person
Manufacturing & Automotive
5 - 7 years of experience
5 days ago
Job Overview by Ladders

Qualifications

  • Master's or Bachelor's degree in a quantitative field (e.g., Statistics, Data Science) with 5-8 years of relevant analytics experience.
  • Proven track record in delivering advanced ML solutions in supply chain or manufacturing.
  • Strong skills in Databricks (Python, SQL, PySpark) and statistical modeling.
  • Experience with building or consuming MCP servers to link AI agents with enterprise system APIs.
  • Hands-on experience in designing multi-agent systems using platforms like Azure AI and AutoGen.
  • Ability to convert complex business problems into ML solutions and effectively communicate results.
  • Excellent stakeholder management and collaboration skills.

Responsibilities

  • Lead advanced data science initiatives focused on supply chain and manufacturing operations.
  • Develop and own machine learning solutions tailored for operational decision-making processes.
  • Build and interpret advanced ML models to identify optimization opportunities in the supply chain.
  • Operationalize analytics solutions using Databricks for large-scale data processing.
  • Design multi-agent AI systems for enhanced decision support in manufacturing contexts.
  • Collaborate with key departments to transform ambiguous problems into structured ML approaches.
  • Create automated AI-enabled analytics workflows to reduce manual effort.

Benefits

  • Flexible work hours and remote work options.
  • Opportunities for professional development and training.
  • Access to cutting-edge technologies and tools for innovation.
  • Collaborative and inclusive company culture.
  • Comprehensive health and wellness programs.
Full Job Description
Job Responsibilities

  • Lead complex data science and machine learning initiatives supporting supply chain, manufacturing operations, capacity planning, demand forecasting, and operational decision-making.
  • Design, develop, and own advanced ML solutions - including predictive models, time-series forecasting, optimization, and decision-support systems - scoped to supply chain and manufacturing use cases.
  • Build, train, evaluate, and interpret machine learning models (regression, classification, clustering, forecasting) to quantify supply chain drivers, surface optimization opportunities, and improve operational outcomes.
  • Develop and operationalize analytics and ML solutions using Databricks (Python / SQL / PySpark) for large-scale data processing, model development, and experimentation.
  • Design and build multi-agent AI systems - including orchestrator-executor architectures, tool-calling agents, and RAG-based decision support - using frameworks such as Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph.
  • Implement and extend solutions using the MCP to enable AI agents to access and act on enterprise data systems in supply chain and manufacturing contexts.
  • Apply data science best practices including feature engineering, model validation, performance monitoring, reproducibility, and documentation.
  • Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT to translate ambiguous business problems into structured ML and AI approaches.
  • Develop and maintain self-service, automated, and AI-enabled analytics workflows that reduce manual effort and improve decision latency.
  • Leverage Azure AI Foundry, Microsoft Copilot Studio, and Microsoft 365 Copilot extensibility to prototype and deploy AI-powered analytics and agent-based decision-support tools.
  • Produce executive-ready insights through clear storytelling, visualizations, and recommendations using Power BI or embedded analytics.
  • Set technical direction, establish reusable ML and AI frameworks, and mentor junior and mid-level data scientists across the team.
  • Ensure high standards of data quality, governance, model validation, and explainability.


Minimum Qualifications

Education & Experience (one of the following):
  • Master's degree in Statistics, Mathematics, Industrial Engineering, Data Science, Computer Science, Engineering, or a related quantitative field with 5+ years of relevant data science/analytics experience, OR
  • Bachelor's degree in the same or related fields with 8+ years of relevant data science / analytics experience.


Technical:
  • Demonstrated track record delivering advanced ML and data science solutions in supply chain, manufacturing, or industrial domains.
  • Strong hands-on experience with machine learning and statistical modeling - development, interpretation, and operational business application.
  • Strong proficiency in Databricks (Python, SQL, PySpark, Delta Lake).
  • Hands-on experience with the MCP - building or consuming MCP servers/clients to connect AI agents to enterprise data systems, APIs, or ERP modules.
  • Hands-on experience with multi-agent system design - architecting multi-agent systems using AutoGen, Semantic Kernel, LangChain/LangGraph, or Azure AI Agent Service; orchestrator-executor patterns, tool calling, memory management, and agent coordination.
  • Compulsory - must have hands-on experience with one or more of the following:
    • Azure AI Foundry
    • Microsoft Copilot Studio
    • Microsoft 365 Copilot extensibility
    • Microsoft Power Platform (Power Automate, Power BI)
  • Ability to translate complex business problems into ML / AI solutions and communicate findings to both technical and executive audiences.
  • Strong stakeholder management and cross-functional collaboration skills.


Preferred Qualifications

  • Experience operationalizing ML models into production in supply chain or manufacturing environments.
  • Familiarity with SAP ECC / S/4HANA supply chain and manufacturing modules (MM, PP, PM, SD).
  • Strong Power BI experience - semantic modeling, performance optimization, executive dashboard design.
  • Exposure to MLOps on Azure (Azure ML, MLflow, Databricks Asset Bundles, CI/CD for analytics artifacts).
  • Experience designing operational KPI frameworks (MAPE, OTIF, service level, OEE, downtime).
  • Experience with statistical / simulation methods (Monte Carlo, scenario analysis, sensitivity analysis) applied to operations and supply chain.
  • Familiarity with Palantir Foundry (pipelines, ontology, Workshop, AIP).
  • Proven experience mentoring data scientists or leading end-to-end analytics initiatives.
  • Familiarity with cloud-native data architectures and governed data platforms.


Other

About Hexion

Hexion is a global specialty chemicals company that produces a range of resins, adhesives, and other chemical products. The company's products are used in a variety of industries, including automotive, construction, and electronics. Hexion was formed in 2005 through the merger of two chemical companies, Borden Chemical and Resolution Performance Products. The company is headquartered in Columbus, Ohio and has operations in North America, Europe, and Asia.
Learn more about Hexion
Size
4,300 employees
Industry
Manufacturing & Automotive
Founded
1857
* Ladders Estimates

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