Note: The job is a remote job and is open to candidates in USA. Corning Incorporated is one of the world’s leading innovators in glass, ceramic, and materials science. They are seeking a Data Scientist to develop AI and machine learning solutions that enhance efficiency and improve decision-making within the finance function of a large organization.

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 methods—including time series analysis, Bayesian techniques, tree-based models, clustering, deep learning, NLP, and Generative AI—to solve complex cross-functional finance business problems
• Implement best practices across the full model lifecycle, including problem framing, data quality assessment, feature engineering, validation, interpretability, monitoring, documentation, and reproducibility
• Evaluate existing models, metrics, and workflows critically, and recommend enhancements to improve robustness, scalability, and operational efficiency
• Partner with ML Engineers and Data Engineers to transition prototypes and research into production-ready, governed AI solutions
• Translate analytical findings into clear business insights and recommendations for senior finance leaders and executives
• Coach and mentor embedded Finance data scientists on modeling standards, reusable approaches, and best practices
• Stay informed on emerging AI/ML research, tools, and methodologies, and identify opportunities to adopt innovations that deliver measurable business value and can be operationalized responsibly
• Communicate learnings, model performance, and standards through presentations, documentation, and knowledge-sharing forums
• Compile, integrate, and prepare internal and external data sources for advanced analysis and modeling
• Contribute high-quality, well-documented code to shared repositories in accordance with enterprise standards

Skills

• Minimum of 5 years of experience applying data science and machine learning methods to solve complex business problems
• Master's degree or PhD in a quantitative discipline such as Data Science, Statistics, Mathematics, Computer Science, Economics, or Finance
• Academic coursework in applied statistics, machine learning, or data science
• Demonstrated ability to work independently while contributing effectively within highly collaborative, cross-functional teams
• Proven success in converting research and analytical work into production-ready solutions
• Strong curiosity and willingness to challenge conventional processes and assumptions
• Self-motivated with a commitment to continuous learning and staying current with evolving AI/ML tools and practices
• Ability to communicate complex technical analysis clearly and effectively to senior business stakeholders
• Strong proficiency in Python and the broader Python AI/data science ecosystem
• Experience with Git-based source control, including platforms such as GitHub or GitLab
• Coursework or demonstrated interest in Finance, Economics, or Operations Management is a plus
• Familiarity with Databricks and cloud-based machine learning platforms such as AWS or Azure is preferred
• Experience with distributed computing frameworks such as Spark is a plus
• Prior publications or conference presentations in quantitative or technical fields are a plus

Company Overview

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