Lead Data Scientist - Remote

10h10 hours ago

Hexion Inc.

Columbus, US · Full-time · $160,000 – $220,000

About this role

At Hexion, we push boundaries, rethink possibilities, and create real impact. We activate science to deliver progress—developing breakthrough solutions that strengthen industries, protect communities, and drive a more sustainable future. Bold thinkers, problem-solvers, and innovators come together to shape what’s next.

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.

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. Set technical direction, establish reusable ML and AI frameworks, and mentor junior and mid-level data scientists across the team.

We invest in innovation, sustainability, and continuous development—equipping you with the tools, training, and opportunities to excel. With an unwavering commitment to safety, partnership, belonging, and impact, we empower you to lead change and strengthen industries worldwide.

Requirements

Experience building, training, evaluating, and interpreting machine learning models such as regression, classification, clustering, and forecasting.
Proficiency developing and operationalizing analytics using Databricks with Python, SQL, and PySpark for large-scale data processing.
Hands-on experience designing multi-agent AI systems with frameworks such as Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph.
Ability to apply data science best practices including feature engineering, model validation, performance monitoring, reproducibility, and documentation.
Skill developing self-service, automated, and AI-enabled analytics workflows that reduce manual effort and improve decision latency.
Experience leveraging Azure AI Foundry, Microsoft Copilot Studio, and Microsoft 365 Copilot extensibility to prototype and deploy AI-powered tools.

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.
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 Azure AI Foundry, AutoGen, Semantic Kernel, or LangChain/LangGraph.
Partner with Supply Chain & Procurement leadership, Manufacturing Ops, Process Engineering, Demand Planning, and IT to translate business problems into structured ML and AI approaches.
Produce executive-ready insights through clear storytelling, visualizations, and recommendations using Power BI or embedded analytics.
Ensure high standards of data quality, governance, model validation, and explainability.