Director, Accelerator Innovation and Emerging Tech Lead

Mars•Chicago, IL

1d•$153,600 - $211,200

About The Position

Reporting directly to the Chief Digital Information Officer, you will serve as the visionary spark and primary voice for technology innovation at KIND and Mars Snacking. In this high-impact role, you will turn advanced capabilities—such as AI/ML, agentic systems, and digital twins—into sequenced, practical roadmaps, leading hands-on pilots and shaping our overall digital strategy. Your influence will stem from your peerless domain knowledge, your ability to build trust across diverse teams, and your knack for translating complex technical opportunities into massive business value for Supply Chain, Demand, Growth, and Finance. As a deep subject matter expert and key individual contributor, you will bridge the gap between emerging technology and real commercial outcomes. You will help set the vision and establish best-practice guidelines that align with our digital strategy, working closely with DT Business Relationship Managers and business leads. If you are an entrepreneurial builder who thrives on autonomy, loves mentoring others, and wants to shape how a global leader snacks smarter, this is your opportunity to make a lasting impact.

Requirements

Bachelor’s degree in Computer Science, Data Science, or equivalent (Master’s degree or specialized postgraduate AI certification is a distinct advantage).
8+ years of progressive, hands-on experience in Analytics, Automation, and AI/ML, with demonstrable architectural depth and a primary focus on modern enterprise AI deployments.
Direct, hands-on experience developing, deploying, and governing models within modern enterprise data platforms (such as Databricks, Azure ML, or AWS SageMaker), including robust MLOps practices.
Proven experience building and governing agentic AI systems covering orchestration, tool integration, permission scoping, and escalation design.
Practical judgment to match the right tool to the business context, paired with working knowledge of RPA, Process Mining, and Low-Code/No-Code platforms.
Fluency in data product design, data modeling, Lakehouse architectures, and enterprise governance frameworks (such as Unity Catalog or equivalent) spanning both structured and unstructured AI assets.
Outstanding executive-level communication skills, with the ability to distill complex architectural decisions into a crisp business case, ROI projection, or strategic investment recommendation.
Strong business mindset to evaluate emerging technologies through the rigorous lens of value, operational efficiency, and risk mitigation, rather than a purely technical perspective.

Nice To Haves

Deep familiarity with CPG or manufacturing business processes, specifically in Plan-to-Deliver (Supply Chain), Order-to-Cash/Trade (Commercial), and Record-to-Report (Finance) domains.
Exceptional capability to engage credibly across disparate business functions by translating complex technical concepts into commercial value for planners, sales leads, finance partners, and data scientists alike.
Proven track record of shaping organizational priorities as an individual contributor through thought leadership, peer relationships, and evidence-based advocacy.
Entrepreneurial spirit, ownership mindset, and a genuine desire to make the world a kinder place—committing to always spreading and celebrating kindness.

Responsibilities

Build and manage a prioritized pipeline of emerging technology use cases, evaluating each against business impact and technical feasibility.
Lead structured technology assessments and pilots, defining success criteria and delivering evidence-based go/no-go recommendations.
Build trusted peer relationships across Digital Technologies, Commercial, Growth, Supply Chain, and Finance to influence priorities through expertise and results.
Represent the innovation agenda in cross-functional forums, presenting clear use cases, pilots, and roadmaps to senior business and IT leaders.
Provide expert guidance on AI/ML platforms, data products, automation, and digital twins in partnership with enterprise architects and data engineers.
Monitor emerging tools, academic research, and competitor capabilities to maintain a forward-looking 12–18-month view of technology trends.
Create a shared internal knowledge base, lead communities of practice to build AI/ML literacy, and mentor IT colleagues addressing AI and automation challenges.