Senior Financial Analyst

Hexion Careers•Worthington, OH

12d

About The Position

Hexion is hiring a Senior Financial Analyst to lead the application of AI and modern analytics across our Global FP&A function. We are looking for a builder who has already delivered measurable wins with AI tools and now wants to apply that capability to the world of finance. You will design, prototype, and deploy AI-enabled solutions that transform how our finance team works — automating recurring analysis, accelerating cycles, and unlocking depth that wasn’t feasible before. Roughly a third of the role is grounded in traditional FP&A. You will own core financial planning and analysis work — supporting the monthly close, building budgets and forecasts, producing management and variance reporting, and partnering with the business on profitability and scenario planning. This is the foundation your AI work makes faster and sharper, and it keeps you close to the real financial decisions the company is making.

Requirements

A demonstrated track record of deploying solutions with modern AI tools (Microsoft Copilot, ChatGPT, Claude, custom agents, or similar) that delivered measurable results — be ready to show what you built and the impact it had.
Hands-on fluency designing and refining prompts, chaining AI into workflows, and validating outputs for accuracy and reliability.
Strong technical foundation: Power BI / Power Query, with the ability to work across large, complex datasets and enterprise systems (SAP a plus).
A builder’s instinct — you spot a manual process and automate it, and you measure the value you create.
Experience in or genuine working knowledge of financial analysis — profitability, P&L modeling, scenario planning, or forecasting. This can come from a finance role, an adjacent analytical role, or strong self-directed work.
Roughly 5 years of professional experience overall, with meaningful exposure to financial or commercial problems.
Advanced Excel and financial modeling skills, or the demonstrated ability to ramp quickly.
Bachelor’s degree in a quantitative field (Finance, Economics, Computer Science, Engineering, Data Science, or related). Industrial, chemicals, or manufacturing exposure a plus.
Curious by default — you ask “why” and “what if,” and you’re always testing the next tool or technique.
Acts with autonomy — you don’t wait to be told what to build next; you find the problem worth solving.
Drives consensus — you can hold a point of view and bring people along, especially when the answer is uncomfortable.
Partners well with commercial teams — you speak their language, respect their pace, and earn their trust.
Bias toward action — you’d rather ship a useful 80% answer this week than a perfect one next quarter.

Nice To Haves

SAP a plus
Industrial, chemicals, or manufacturing exposure a plus

Responsibilities

Deploy AI-enabled finance solutions — automating recurring analysis, accelerating close cycles, improving forecast accuracy, and unlocking new analytical depth that wasn’t feasible before.
Own the lifecycle — from identifying a high-value use cases, to prototyping with modern AI tools, to validating outputs and shipping a reliable, repeatable workflow.
Champion AI best practices across Finance — prompt and agent design, model validation, data quality, and responsible, auditable AI use.
Continuously expand the toolkit by replacing manual, error-prone processes with smarter, faster, more scalable approaches — and measuring the impact.
Turn messy, large-scale datasets into insights using AI tools (Microsoft Cowork, Copilot Studio) building dashboards and pipelines that the business can trust.
Translate analytical output into clear narratives — what changed, why it changed, and what we should do about it.
Apply your solutions to real financial problems — profitability analysis across products, customers, and regions; scenario planning; and forecasting that stress-tests pricing, volume, and raw material assumptions.
Partner with commercial teams (Sales, Marketing, Product Management) to translate financial and analytical signals into pricing, mix, and go-to-market actions.
Drive consensus across functions when the data points to a tough call, bringing stakeholders along with rigor and clarity.