Senior Financial Analyst, Finance AI & Automation

Lenovo•Morrisville, NC

About The Position

Lenovo is seeking a Senior Financial Analyst, Finance AI & Automation, to serve as a hands-on Finance transformation lead in a multinational organization. The role combines traditional FP&A responsibilities—including planning, forecasting, variance analysis, management reporting, and business partnership—with a primary focus on using technology, automation, and AI to streamline Finance processes and improve efficiency. The successful candidate will help develop an AI-minded Finance operating model and turn recurring pain points and Excel-based processes into practical, scalable solutions using Microsoft Copilot, Power BI, Power Query, Power Automate, AI agents, prompting, and other approved technologies. The role leads discovery, prototyping, testing, implementation, documentation, and adoption in partnership with Finance, IT, data, security, and system owners. Lenovo is looking for someone who has delivered AI, automation, or digital-transformation solutions in a Finance environment.

Requirements

Bachelor’s degree in Finance, Accounting, Economics, Business, Information Systems, or a related field.
At least 5 years of experience in technology, manufacturing, consulting, or another complex global organization.
At least 5 years of finance experience.
Strong grounding in core FP&A work, including financial modeling, planning, forecasting, variance analysis, management reporting, and business partnership.
Demonstrated experience delivering AI, automation, analytics, or digital-transformation solutions for Finance, from problem definition through implementation and user adoption.
Hands-on experience with Microsoft Copilot and Power BI, plus practical experience with prompts, workflow automation, or AI agents in a business setting.
Ability to document Finance requirements, map processes and data flows, define acceptance criteria, test outputs, and work effectively with IT and data teams.
Strong communication, facilitation, training, change-management, and commercial business stakeholder-influence skills.

Nice To Haves

MBA, CPA, CFA, or relevant Finance, analytics, automation, or technology certification.
Understanding of internal controls, reconciliation, auditability, responsible AI, data privacy, access management, and Finance data governance.
Experience leading multi-year roadmaps, process improvement, project management, or enterprise change initiatives.

Responsibilities

Identify and prioritize valuable automation opportunities across planning, forecasting, reporting, close, reconciliations, data preparation, and routine analysis.
Inventory legacy Excel workbooks, linked files, macros, reports, and recurring workflows, and redesign them with appropriate tools.
Build and implement Finance solutions using Microsoft Copilot, Power BI, Power Query, Power Automate, AI agents, prompts, and other approved low-code or analytics tools.
Design reusable prompts, agent instructions, workflows, templates, and quality checks to help Finance complete routine work faster and more consistently.
Translate finance logic and business rules into functional requirements, data models, dashboards, automated workflows, and controlled AI-assisted processes.
Prototype solutions with Finance users, validate outputs against trusted sources, and transition successful pilots into supported, documented production workflows.
Measure value through time saved, cycle-time and error reduction, adoption, control effectiveness, and improved decision support.
Partner with business, Sales, and Operations leaders, translating financial and operational data into recommendations.
Evaluate growth opportunities, business risks, resource trade-offs, and performance drivers through financial analysis.
Communicate financial, operational, and reporting insights to technical and non-technical stakeholders.
Translate Finance pain points into technical requirements and explain technical options, trade-offs, and risks in practical Finance terms.
Partner with Finance Systems, IT, data engineering, security, risk, and system owners on architecture, source-data access, permissions, deployment, support, and governance.
Gather user feedback, resolve defects, and continuously improve solutions after launch.