Data Scientist

Corning • City of Corning, NY

11d • $109,335 - $150,336 • Hybrid

About The Position

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.

Requirements

• Minimum of 5 years of experience applying data science and machine learning methods to solve complex business problems.
• MS or PhD in a quantitative discipline (Data Science, Statistics, Mathematics, Computer Science, Economics, Finance).
• Coursework in applied statistics, machine learning, or data science.
• Strong ability to work independently while contributing effectively to highly collaborative, cross-functional teams.
• Proven ability to convert research and analytical work into production-ready solutions.
• Demonstrated curiosity and willingness to challenge traditional processes and assumptions.
• Self-driven with a commitment to continuous learning, including staying current with modern AI/ML practices and tooling.
• Ability to present complex technical analysis to senior-level business stakeholders.
• Strong proficiency in Python and the Python AI/data science ecosystem.
• Experience with Git-based source control (GitHub, GitLab).

Nice To Haves

• Coursework or demonstrated interest in Finance, Economics, or Operations Management are a plus.
• Prior publications or conference presentations in quantitative fields are a plus.
• Familiarity with Databricks and cloud ML platforms (AWS, Azure) is a plus.
• Experience with distributed computing frameworks (Spark) is a plus

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 across the model lifecycle (problem framing, data quality, feature engineering, validation, interpretability, monitoring, documentation, and reproducibility) to ensure solutions are robust, explainable, and governable.
• Critically evaluate existing models, metrics, and workflows; recommend and implement improvements to increase robustness, scalability, and operational efficiency.
• Collaborate with ML Engineers and Data Engineers to convert research and prototypes into production-ready, governed AI solutions.
• Translate analytical results into clear insights and recommendations for senior finance leaders and executives.
• Coach and mentor embedded and junior data scientists on modeling standards, reusable patterns, and best practices.
• Stay current on state-of-the-art AI/ML research and tooling; experiment with emerging methods and drive adoption where they provide clear business value and can be operationalized responsibly.
• Share learnings, model performance, and standards through presentations, documentation, and knowledge-sharing forums.
• Compile, integrate, and prepare internal and external datasets for advanced modeling.
• Contribute high-quality, well-documented code to shared repositories following enterprise standards.

Benefits

• Company-wide bonuses and long-term incentives align with key business results and ensure you are rewarded when the company performs well.
• 100% company-paid pension benefit with fixed contributions that grow throughout your career.
• Matching contributions to your 401(k) savings plan.
• Medical, dental, vision, paid parental leave, family building support, fitness, company-paid life insurance, disability, disease management programs, paid time off, and an Employee Assistance Program (EAP) to support you and your family.
• Recognition program to celebrate successes and reward colleagues who make exceptional contributions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior