[Remote] Lead Data Scientist - US Remote
Note: The job is a remote job and is open to candidates in USA. Hexion Inc. is a company focused on innovation and sustainability, aiming to create impactful solutions across various industries. They are seeking a Lead Data Scientist to lead complex data science and machine learning initiatives, particularly in supply chain and manufacturing operations, while developing advanced ML solutions and collaborating with cross-functional teams.
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
Skills
- 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
- 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
- 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
Company Overview
Company H1B Sponsorship