Data Scientist

Data Scientist

** Date:
** Jul 14, 2026

*
* Location:

** Corning, NY, US, 14831

** Company:
** Corning

Requisition Number: 74453

** The company built on breakthroughs. ​ *
* ** Join us.​ *
* 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.​  

Come break through with us. 

Corning's businesses are ever-evolving to best serve our customers, industries, and consumers. Today, we accelerate and transform life sciences, mobile consumer electronics, optical communications, display, automotive, and solar markets. We are changing the world with:

+ Trusted products that accelerate drug discovery, development, and delivery to save lives

+ Damage-resistant cover glass to enhance the devices that keep us connected

+ Optical fiber, wireless technologies, and connectivity solutions to carry information and ideas at the speed of light

+ Precision glass for advanced displays to deliver richer experiences

+ Auto glass and ceramics to drive cleaner, safer, and smarter transportation

+ Solar polysilicon, wafers, and innovative photovoltaic modules, enabling low-cost solar energy solutions

The Data Scientist role is an exciting opportunity to join Corning's Data Science & Insight (DSI) team, building AI/ML solutions for finance to drive efficiency, insight, and better decision-making across a large and diverse Fortune 500 organization. This position sits within the Finance Function and supports digital transformation across corporate finance and the enterprise. A key focus is designing and delivering enterprise-grade, reusable AI/ML models and frameworks that can be leveraged across finance to address a wide range of business challenges.

The team applies expertise in statistics, data science, machine learning, AI, MLOps, and corporate finance, and projects are executed collaboratively with strong individual ownership.

Using advanced modeling techniques, the Data Scientist enables objective, insightful analysis of stakeholders at all levels, including senior leadership. The role requires strong capability in applying robust data science and machine learning methods to complex finance problems, including time series, Bayesian modeling, supervised and unsupervised learning, reinforcement learning, deep learning, NLP, and GenAI. The candidate will develop scalable, reusable solutions and help advance modeling standards across finance.

The position is hybrid-remote, with the expectation of coming to the Corning HQ office for in-person meetings as needed.

** Role Context*
* The Data Scientist is a core member of the centralized Digital Center AI team supporting Finance. The role builds and maintains shared AI capabilities-including forecasting, predictive modeling, NLP/GenAI, prescriptive analytics, and pattern recognition-for use across FP&A, Treasury, Controllership, Tax, and Risk. Success in this role requires a strong focus on scalability, robustness, and responsible deployment, with consistent application of industry best practices in model development, validation, documentation, governance, and MLOps.

The Data Scientist is also expected to stay current on AI/ML advancements and translate relevant innovations into practical, enterprise-ready improvements.

** Day to Day Responsibilities*
* + Design, develop, and validate foundational, reusable AI/ML models and frameworks that can be leveraged across multiple finance functions.

+ Apply advanced statistical and machine learning techniques (e.g., time series, Bayesian methods, tree-based models, clustering, deep learning, NLP, GenAI) to solve complex, cross-finance business problems.

+ Implement industry best practices…