Digital Finance Analyst

About the role

The Digital Finance Analyst is an embedded member of a Finance delivery team and a participant in Corning's Digital Finance Program (DFP). This position sits within the Finance Function and supports digital transformation across corporate finance and the enterprise.

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.
• Auxiliary 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.

Requirements

• 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.
• 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.
• 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.