Sr Manager, Analytics & AI, Finance & Corporate

Ferrara•Chicago, IL

49d•Hybrid

About The Position

The Senior IT Product Manager – Analytics (Commercial & Corporate Functions) is a senior, business-facing technology leader responsible for defining, delivering, and scaling enterprise analytics products that enable data-driven decision-making across Commercial (Sales, Marketing, Revenue Growth Management, Customer, Pricing) and Corporate (Finance, HR, Legal, Procurement, Strategy) functions. This role blends product management rigor, analytics and data platform leadership, and senior stakeholder partnership. The Sr. IT Product Manager owns the end-to-end analytics product lifecycle—from strategy and roadmap through delivery, adoption, and value realization—while ensuring alignment with enterprise data, AI, security, and technology standards. Success is measured by business impact, adoption, and the ability to translate complex functional needs into scalable, trusted analytics capabilities.

Requirements

Bachelor’s degree in Information Technology, Computer Science, Engineering, Business, or equivalent experience
7+ years of progressive IT experience, including analytics, data platforms, or enterprise systems
Demonstrated experience delivering enterprise-scale analytics or data products
Strong understanding of Commercial and/or Corporate business processes and data
Proven ability to influence senior business and technology leaders

Nice To Haves

Experience with SAP S/4HANA and enterprise commercial or financial data domains
Experience with cloud-based data platforms, modern BI tools, and AI/ML use cases
Experience leading large-scale transformation or digital programs
Certifications in Product Management, Analytics, Data Engineering, or Agile delivery

Responsibilities

Define and maintain the analytics product strategy and roadmap supporting Commercial and Corporate functions
Partner with senior business leaders to translate strategic priorities into scalable analytics capabilities
Develop business cases, value hypotheses, and success metrics for new analytics investments
Balance innovation, speed-to-value, and platform standardization
Lead cross-functional teams (Data Engineering, BI, Architecture, Data Science, Vendors) to design, build, test, and deploy analytics products
Manage multiple concurrent initiatives across functions while maintaining alignment to enterprise priorities
Ensure strong delivery discipline across Agile and hybrid delivery models
Provide visibility into risks, dependencies, timelines, and outcomes; escalate as needed
Enable self-service analytics through reusable, well-governed data and semantic layers
Drive adoption of advanced analytics and AI-enabled use cases across Commercial and Corporate domains
Lead insight-driven problem solving, root-cause analysis, and performance measurement
Support analytics maturity and upskilling of business users
Partner with Enterprise Architecture to shape analytics and data platform direction
Review solution designs to ensure alignment with enterprise standards, scalability, and security
Guide integration across SAP and non-SAP platforms and enterprise data products
Ensure analytics solutions support end-to-end business processes and decision flows
Embed enterprise-grade security, privacy, and compliance controls into analytics solutions
Ensure adherence to corporate policies, regulatory requirements, and data governance standards
Partner with Risk, Security, and Legal teams to assess technologies and vendors
Manage strategic delivery and solution partners as an extension of internal teams
Ensure vendor performance, accountability, and alignment to business outcomes
Build trusted relationships across business, IT, and executive stakeholders
Communicate clearly with senior audiences on trade-offs, risks, and recommendations
Owns prioritization of analytics initiatives and product backlog within the domain
Defines scope, sequencing, and delivery approach for analytics products
Escalates and resolves competing functional priorities
Influences enterprise analytics and data platform decisions