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Corning

Specialty glass, ceramics, and tech components

Supply Chain Analytics Specialist - Supply Chain Analytics, AI/ML

Applied Machine Learning +1Updated on Nov 14
Full-timeGurugram, Haryana, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's or master's degree in engineering, computing, science, or a related field.
  • At least 5–6 years of experience in a similar role.
  • Working proficiency in Python, including pandas, NumPy, and scikit-learn, for data manipulation, statistical analysis, and building predictive or prescriptive models.
  • Hands-on experience applying Generative AI and large language model tools, such as Microsoft Copilot, Azure OpenAI, ChatGPT, or Claude, to business or analytics workflows, including prompt engineering fundamentals.
  • Applied knowledge of machine learning and statistical techniques, such as KMeans and Gaussian Mixture Models, to generate actionable business insights.
  • Familiarity with cloud data platforms such as Azure, Databricks, or Snowflake, and modern data pipeline and ETL practices, including Delta Lake or Parquet-based architectures.
  • Strong practitioner-level ability with business intelligence tools, especially Power BI, for data visualization and recommendations.
  • Experience in manufacturing or supply chain industries.
  • Ability to explain complex technical solutions in clear, business-friendly terms to stakeholders at all levels.
  • Ability to collaborate with team members and functional and business stakeholders to deliver results.
  • Ability to manage multiple projects and priorities to meet deadlines.
  • Critical thinking to evaluate, validate, and responsibly apply AI-generated outputs and recommendations.

Responsibilities

  • Translate business needs into technical specification documents.
  • Design, prototype, and deploy Generative AI-powered solutions, such as AI agents, copilots, and retrieval-augmented generation (RAG) pipelines, to automate insight generation and augment analyst decision-making across Global Supply Management.
  • Apply prompt engineering and large language model orchestration techniques to build reliable, auditable AI workflows using enterprise data.
  • Apply unsupervised machine learning and statistical techniques to real supply chain datasets and translate results into actionable, business-ready recommendations.
  • Evaluate and responsibly deploy AI and machine learning outputs, using judgment to validate accuracy, bias, and business relevance before sharing insights with stakeholders.

Desired Qualifications

  • Experience building or integrating AI agents or agentic workflows using frameworks such as LangChain.
  • Exposure to MLOps practices, including model versioning, monitoring, and continuous integration and continuous delivery for machine learning, and to version control with Git.
  • Understanding of data governance and responsible AI principles, including bias, explainability, and data privacy, in an enterprise setting.
  • Experience with Microsoft Fabric or other unified analytics platforms.

About the Company

Corning

Specialty glass, ceramics, and tech components

Corning develops and manufactures specialty glass, ceramics, and related components for a range of industries. Its engineered glass and ceramic materials are produced and integrated into devices and systems such as smartphone screens, high‑performance displays, optical networks, automotive emissions controls, and life‑science equipment. The company differentiates itself with a broad portfolio across multiple markets, material science expertise, reliable supply, and end‑to‑end components and systems. Its goal is to help customers achieve performance and reliability by providing durable, high‑quality materials and connected solutions that scale with growing demand.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Corning, NY
Founded
1851

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