Senior Director, Finance AI SME, FP&A and Forecasting Transformation - Eden Prairie, MN preferred, Remote considered

UnitedHealth Group is a health care and well-being company that's dedicated to improving the health outcomes of millions around the world. We are comprised of two distinct and complementary businesses, UnitedHealthcare and Optum, working to build a better health system for all. Here, your contributions matter as they will help transform health care for years to come. Make an impact with a team that shares your passion for helping others. Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together. The Senior Director, Finance AI SME, FP&A and Forecasting Transformation will serve as a senior finance subject matter expert embedded within Finance AI transformation pods. This leader will partner closely with Finance, Data, Technology, Risk and Controls, and business stakeholders to blueprint current-state and future-state finance processes, translate business requirements into agent-ready workflows, and help develop proof-of-concept AI systems that can be validated, governed, and scaled. This role is designed for a senior finance leader with deep FP&A and forecasting experience who can bridge the gap between business finance and technical delivery teams. The individual will bring practical expertise in enterprise forecasting, variance analysis, financial planning, driver-based modeling, performance reporting, and executive decision support. The role requires the ability to understand how finance work is performed today, identify where AI and automation can materially improve speed, quality, controls, and insight, and help convert future-state designs into tangible AI-enabled solutions. The Senior Director will operate in a cross-functional pod model, working side by side with data engineers, solution architects, forward deployed engineers, AI/ML resources, risk and controls partners, and business finance leaders. The person will not simply advise from the sidelines. They will be expected to lead hands-on blueprinting sessions, define use-case requirements, pressure-test data and control assumptions, validate prototype outputs, and ensure that AI systems are solving real finance problems in a way that is accurate, explainable, auditable, and adoptable. The purpose of this role is to provide senior-level FP&A and forecasting expertise to Finance AI pods that are redesigning core finance processes and developing proof-of-concept AI systems. The Senior Director will help move Finance from periodic, manual, and fragmented forecasting and analysis processes toward more continuous, driver-based, data-enabled, and AI-supported decision intelligence. The role will focus on three integrated mandates:Blueprint the current state. Understand and document existing FP&A and forecasting activities, including process flows, data inputs, handoffs, manual workarounds, estimation methods, controls, outputs, and decision pointsDesign the future state. Partner with business and technology stakeholders to define how forecasting, variance analysis, scenario modeling, performance reporting, and decision support should operate when AI, data, controls, and human judgment are designed together from the beginningDevelop and validate AI proof-of-concept systems. Translate finance requirements into clear prototype designs, partner with data and technology teams during development, validate outputs against business expectations, and help determine whether POCs should be killed, refined, scaled, or transitioned to the AI Factory for productization You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week. Primary Responsibilities: Finance SME Leadership in Pod DeliveryServe as a senior Finance SME within cross-functional Finance AI pods focused on FP&A, forecasting, performance reporting, and decision intelligencePartner with pod leads, business finance leaders, data teams, solution architects, and engineering resources to define the business problem, target outcomes, scope, requirements, and success criteria for each POCBring practical FP&A judgment to AI design decisions, ensuring prototypes reflect how finance leaders actually forecast, analyze, explain, and make decisionsAct as the translator between finance users and technical teams, converting business needs into clear, testable requirements for AI-enabled workflowsHelp ensure pod work remains focused on high-value finance problems rather than disconnected technology experimentation Current-State BlueprintingLead structured blueprinting sessions with Finance, business, data, and technology stakeholders to map current-state forecasting and FP&A processesDocument key process steps, business owners, data sources, systems, handoffs, manual workarounds, spreadsheet dependencies, control points, approvals, recurring pain points, and decision outputsIdentify the root causes of inefficiency, including fragmented data, inconsistent definitions, duplicative reporting, manual variance analysis, delayed business driver inputs, and legacy planning practicesDistinguish between work that is essential judgment, work that can be automated, work that can be redesigned, and work that should be eliminatedPartner with Risk and Controls to identify current control dependencies and determine where future-state AI processes must preserve or strengthen auditability, traceability, and human review Future-State Design and Agent-Ready Workflow DevelopmentDesign future-state FP&A and forecasting workflows that incorporate AI agents, governed data products, certified business definitions, automated insight generation, and human-in-the-loop decision rightsHelp define how evergreen forecasting, driver-based forecasting, variance explanation, scenario planning, and executive insight generation should operate across business segmentsConvert process redesign concepts into agent-ready workflows with clear triggers, inputs, outputs, decision points, exception handling, validation requirements, and escalation pathsPartner with Data and Technology teams to define required data products, semantic layers, model inputs, output expectations, source citations, lineage needs, and evaluation criteriaEnsure future-state designs balance speed and automation with Finance's unique requirements for precision, controls, regulatory readiness, and confidence in financial outputs AI POC Development and ValidationPartner with engineering and data teams to develop POCs for AI-enabled forecasting, variance analysis, bridge narratives, management reporting, planning support, and decision intelligenceDefine practical test cases, expected outputs, comparison baselines, and acceptance criteria for AI-generated forecasts, insights, narratives, and recommendationsValidate prototype outputs against known business results, finance logic, source data, and user expectationsIdentify hallucination risk, inconsistent logic, data gaps, control deficiencies, usability issues, and adoption barriers before POCs move toward scaleRecommend whether POCs should proceed to additional testing, be refined, be redesigned, be paused, or be transitioned to the AI Factory for productization FP&A and Forecasting TransformationBring deep expertise in forecasting methods, planning cycles, driver-based modeling, variance analysis, business performance management, and senior executive reportingHelp redesign forecasting processes to move from static cycle-based planning toward more continuous, signal-based, and business-driver-informed forecastingSupport development of AI-enabled capabilities across medical trend forecasting, cash forecasting, P&L forecasting, segment forecasting, and performance analyticsWork with business finance teams to identify where AI can improve speed of insight, forecast accuracy, scenario analysis, root-cause identification, and decision supportHelp define how forecasting outputs should be consumed by CFOs, segment leaders, business operators, Investor Relations, Treasury, and other stakeholders Data, Controls, and GovernancePartner with Data teams to assess data readiness, data quality, source system limitations, business driver availability, and semantic consistencyEscalate data gaps that prevent reliable AI-enabled forecasting or financial analysisPartner with Risk, Controls, Compliance, Internal Audit, and Finance leadership to ensure future-state AI workflows are explainable, traceable, auditable, and appropriately governedSupport design of human approval gates, output review standards, source documentation, model validation checkpoints, and ongoing monitoring routinesEnsure AI-enabled workflows are built with appropriate consideration for SOX, financial reporting precision, regulatory expectations, and enterprise governance standards Stakeholder Engagement and AdoptionBuild credibility with senior Finance and business leaders by demonstrating solid business judgment, practical finance experience, and command of forecasting and performance managementFacilitate working sessions with business SMEs, Controllers, FP&A leaders, Technology, Data, and Risk partnersTranslate complex AI and data concepts into clear finance implications for senior stakeholdersSupport change management by helping finance users understand how redesigned workflows will improve speed, insight, quality, and capacityCapture adoption barriers, training needs, process changes, and role impacts as AI-enabled workflows are piloted and scaled You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.Required Qualifications: Bachelor's degree in Finance, Accounting, Economics, Business, Data Analytics, or a related field12+ years of progressive finance experience, with significant depth in FP&A, forecasting, business performance management, or enterprise financial planningDemonstrated experience leading or materially contributing to forecasting, planning, variance analysis, management reporting, or decision support in a large, complex enterpriseProven solid understanding of driver-based forecasting, P&L analysis, business metrics, executive reporting, and financial planning processesExperience working across business, finance, technology, and data teams to deliver process improvement, automation, analytics, or transformation initiativesAbility to map complex current-state processes and translate them into simplified future-state operating modelsProven solid analytical and problem-solving skills, with the ability to evaluate data quality, process gaps, business logic, and control implicationsProven solid executive communication skills, including the ability to synthesize complex issues, frame trade-offs, and make clear recommendationsAbility to operate in ambiguity, influence without direct authority, and move work forward across a matrixed organizationProven high degree of ownership, urgency, judgment, and attention to detail Preferred Qualifications:  MBA, CPA, CMA, or equivalent advanced finance, accounting, or analytics credentialExperience with AI, machine learning, automation, analytics products, data products, or digital finance transformationExperience with Oracle EPM, enterprise planning tools, data visualization platforms, financial data marts, Snowflake, Azure, or related enterprise data environmentsExperience designing or implementing driver-based forecasting, rolling forecasts, scenario modeling, or advanced business performance analyticsExperience supporting finance transformation in a regulated environment with SOX, SEC reporting, audit, model governance, or other control considerationsFamiliarity with agentic AI concepts, LLM-enabled workflows, human-in-the-loop controls, retrieval-augmented generation, prompt evaluation, and AI output validationExperience working in a product-oriented or agile delivery model, including POCs, pilots, MVPs, product roadmaps, and adoption measurement *All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy. Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $159,300 - $273,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants. At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives.  UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations. UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.