Data Scientist

Requisition Number: 76036

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Corning is one of the world's leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what's possible.

How do we do this? With our people. They break through limitations and expectations - not once in a career, but every day. They help move our company, and the world, forward.

At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.

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Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry.

This segment is classified into two main product groupings - carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications. The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments and individuals for their own use.

Role Purpose

As a Data Scientist, you will serve as a hands-on applied data science contributor within the Business Intelligence team. You will work closely with market intelligence teammates, business stakeholders, and leadership to develop practical analytical solutions that improve how we understand markets, customers, competitors, and business performance.

This role is focused on applied, decision-oriented data science rather than theoretical or research-based work. Success in this role requires balancing technical rigor with speed, business relevance, and clear communication in a fast-moving, high-visibility environment. You will be expected to move efficiently from business question to usable solution while ensuring outputs are credible, explainable, and grounded in business realities.

You will contribute to the technical rigor of the Business Intelligence team by applying sound data science methods, reproducible workflows, and practical analytical approaches to business problems. This role reports directly to the Director of Forecasting & Analytics within the Business Intelligence organization.

Key Responsibilities

• Develop and deliver applied data science solutions for business intelligence use cases such as forecasting, classification, segmentation, anomaly detection, and other predictive or descriptive analytics.
• Own end-to-end analytical execution, including data ingestion, API integration, transformation of structured and semi-structured data, feature engineering, modeling, validation, and stakeholder-ready output creation.
• Partner with market intelligence teammates and business stakeholders to frame ambiguous questions, define fit-for-purpose analytical approaches, and translate outputs into practical recommendations.
• Select appropriate statistical, machine learning, and AI methods based on business need, data constraints, interpretability, and time-to-insight; avoid unnecessary complexity when simpler approaches are sufficient.
• Apply rigorous validation and reasonableness checks to ensure outputs are accurate, explainable, and aligned with market and business context.
• Build scalable, reusable workflows in Databricks and related tools that improve reproducibility, speed, and team efficiency.
• Prepare clear visualizations, dashboards, and executive-ready materials in Power BI, Excel, and PowerPoint to communicate methods, insights, assumptions, and implications effectively.
• Partner closely with business-facing teammates to strengthen quantitative rigor in market intelligence, competitive intelligence, strategic finance, and economics-oriented analyses.
• Stay current with the evolving data science and AI landscape and contribute ideas for applying new methods and tools where they may create business value.
• Contribute to best practices for experimentation, documentation, model validation, code quality, and reproducible analytical workflows within the BI analytics team.
• Participate in agile delivery, code reviews, documentation, and production support for analytical solutions.

Experiences/Education - Required

• Bachelor's degree in data science, statistics, computer science, economics, operations research, engineering, or related quantitative field
• Minimum 3 years of experience applying data science, machine learning, or advanced analytics to business problems in a production or business-facing environment
• Strong proficiency in Python and SQL, with experience supporting the analytical workflow from data ingestion and preparation through model output and stakeholder-ready delivery
• Advanced proficiency in Excel and PowerPoint, including…