Data Scientist (Remote)

Role Summary

The Data Scientist II / III role is an exciting opportunity to join Corning’s Data Science & Insight (DSI) team. The individual will develop AI and machine learning solutions that enhance efficiency, generate actionable insights, and improve decision-making across a large and complex Fortune 500 organization. This position sits within the Finance function and supports digital transformation initiatives across both corporate finance and the broader enterprise.

Key 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.

Required Education And Experience

• 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.
• Prior publications or conference presentations in quantitative or technical fields are a plus.

Technical Competencies

• 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.
• 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.

Reward

The range for this position is $109,335.00 - $150,336.00 assuming full time status. Starting pay for the successful applicant is dependent on a variety of job-related factors, including but not limited to geographic location, market demands, experience, training, and education.