Sr. Data Scientist

Requisition Number: 74328

 

The company built on breakthroughs. ​  
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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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The global Information Technology (IT) Function is leading efforts to align IT and Business Strategy, leverage IT investments, and optimize end to end business processes and associated information integration technologies.  Through these efforts, IT helps to improve the competitive position of Corning's businesses through IT enabled processes.  IT also delivers Information Technology applications, infrastructure, and project services in a cost efficient manner to Corning worldwide.

 

Position Overview:

The Senior Data Scientist is a highly skilled, experienced analytical professional responsible for leading complex data science initiatives that drive strategic business decisions and operational improvements. Working within the Optical Communications Data and AI organization, this individual applies advanced statistical modeling, machine learning, experimental design, and data visualization to solve high-value problems across manufacturing, supply chain, commercial, and technology functions. The Senior Data Scientist operates with a high degree of independence, mentors junior team members, and serves as a trusted analytical partner to business stakeholders.

A Senior Data Scientist in this role will be considered successful when they have demonstrated the following:

1. Business Impact & Value Delivery: Within the first year, successfully contributes to at least two end-to-end data science projects that deliver measurable, documented business outcomes - such as cost reduction, forecast accuracy improvement, or operational efficiency gains - working collaboratively with senior team members and business stakeholders to validate and communicate results.
2. Model Quality & Growing Technical Independence: Consistently delivers well-documented, reproducible, and validated analytical models that meet defined performance benchmarks, demonstrating increasing independence in model selection, feature engineering, and validation methodology—while actively incorporating feedback from senior data scientists and machine learning engineers to improve solution quality and production readiness.
3. Stakeholder Engagement & Communication Growth: Demonstrates steady growth in cross-functional collaboration and communication skills, proactively engaging with business partners to understand requirements, presenting analytical findings clearly and confidently to technical and non-technical audiences, and earning recognition as a reliable and developing analytical contributor within assigned business functions.

 

Key Responsibilities:

• Advanced Analytics & Modeling
• Design and execute sophisticated analytical solutions, including predictive modeling, statistical analysis, machine learning, and hypothesis-driven research, to address complex business challenges.
• Apply domain expertise to frame, scope, and deliver high-impact data science projects with minimal supervision.
• Lead exploratory data analysis, feature engineering, and model selection for a wide range of business use cases including demand forecasting, quality improvement, pricing, and operational efficiency.
• Business Partnership
• Collaborate closely with business leaders and cross-functional stakeholders to identify opportunities, define analytical requirements, and translate data insights into clear, actionable recommendations.
• Present findings and recommendations confidently to executive and non-technical audiences, emphasizing business impact and decisio