Digital Finance Analyst

Digital Finance Analyst

The Digital Finance Analyst is an embedded member of a Finance delivery team and a participant in Corning's Digital Finance Program (DFP) — an investment in the next generation of finance talent that combines analytical depth, software fluency, and modern data platforms to deliver insight at scale. This position sits within the Finance Function and supports digital transformation across corporate finance and the enterprise. You will enter the program with technical depth and be systematically developed in financial acumen through structured project assignments, embedded learning, and real project ownership — staffed on cross-functional finance projects with a continuous analytics thread, delivering real business outcomes on Corning's data platform. Participants work in close partnership with the DSI Core Team — Corning Finance's centralized AI/ML and data science group — who set technical standards, provide design guidance, and govern code quality for the solutions delivery teams build. This is not a traditional finance role — it is a deliberate investment in people who think in systems, code, and data, and who want to use those instincts to drive business decisions. Financial training is built into the program; no prior finance experience is required. Activities are performed in accordance with relevant accounting principles, standards, and reporting requirements.

The role is a hybrid role, with an opportunity to combine remote and on-site work at Corning's headquarters in Corning, NY or at the Charlotte, NC office.

Career Path

Upon successful completion of the Digital Finance Program, participants will be placed as a Financial Analysts in a quantitative capacity within Corning's Finance organization, applying the technical and financial skills developed during the program to drive data-informed decisions across the function.

Day to Day Responsibilities

• Build and maintain financial models and automated reporting pipelines in Databricks using Python and SQL.
• Design and contribute to Gold-layer finance datasets sourced from operational systems across manufacturing, supply chain, and commercial functions.
• Support FP&A, Accounting, and Business Unit Finance teams with data analysis, variance commentary, and forecast automation.
• Apply machine learning–assisted techniques — including anomaly detection and cost forecasting — to enhance the predictive value of financial outputs.
• Co-develop self-service dashboards for finance and business stakeholders, replacing manual reporting with governed, reusable analytical assets.
• Lead tracking of financial and/or operational metrics and performance, summarizing findings for stakeholders.
• Assist with internal financial reporting, perform comprehensive trend analysis, and lead data mining against governed finance datasets.
• Monitor daily operations of a unit, actively assist to resolve issues, and escalate as appropriate.
• Analyze and prepare financial and budgetary reports, contributing potential insights.
• Execute and support internal and external controls.
• Perform complex, undefined ad hoc analyses and assigned requests from senior management, leveraging data, automation, and a developing understanding of financial responsibilities within an assigned business unit.
• Complete a capstone project that identifies a high-effort manual finance process, automates it on the platform, and quantifies the business impact.

Required Work / Education

• BS or MS degree in Computer Science, Data Science, Finance, Economics, Statistics, Engineering, or a related quantitative field.
• A minimum of 1 year in a data, analytics, software, or technology role.
• No prior finance experience required — financial training is built into the program.
• Coursework or demonstrated interest in business, economics, or accounting is a plus.

Required Qualifications

• Proficiency in Python and SQL for data manipulation, automation, and analysis.
• Experience with cloud-based data platforms; Databricks experience is a strong differentiator.
• Familiarity with Git and notebook-based development.
• Practical experience using AI Code Assistants (e.g., Copilot, Claude) to accelerate development.
• Ability to build dashboards or visualizations for analytical decision support.
• Experience analyzing data, synthesizing insights, and communicating results to varied audiences.
• Experience using data mining tools and methodologies to produce trend analysis and perform ad hoc research.
• Experience resolving issues related to data analysis and report preparation.
• Experience supporting components of ambiguous and unstructured requests, assisting with obtaining and analyzing data.
• Experience coordinating with and communicating technical concepts to non-technical audiences (e.g., finance, operations, production, floor supervisors) to execute projects.
• Experience developing strategic networks outside of one's home function to build manufacturing and production process expertise.
• Genuine curiosity about why businesses make decisions, not just what the data shows.
• Comfortable structuring ambiguous problems and working without a predefined playbook.
• Collaborative by default — comfortable working across finance, data engineering, and operations.

Desired Qualifications

• Experience contributing to components of large projects.
• Experience working with colleagues from o