Qualifications
Responsibilities
Benefits
Summary:
This is best understood as anenterprise AI measurement, insights, and enablement role—not a model-building role. The core mandate is toempowerCencora’semployees to use AI responsibly, profitably, and well,andmeasurethe value that AI adds toCencora. Whilethis role includevarious tasks related toAI enablement,such as community-building, supportingresponsible use,and participating in technology rollout efforts,a particular focus is tomeasure how AI adoption is impacting Cencora andtranslate results into decision-ready insight for leaders. The role blendsmeasurement strategy, cross-functional advisory work, and hands-on analytics execution. Success depends on linking AI adoption and usage data toreal businessoutcomes such as productivity, quality, cost reduction, risk reduction,proficiency, and change adoption rather thanstopping atactivity metrics alone.
Responsibilities:
The roles central responsibility is toassistwith AI enablement programs including thematuration ofenterprise AI measurement frameworkcovering:
adoption
engagement
proficiency
responsible use
value realization
ROI across multiple AI tools and platforms
AI measurement framework design
The role expects someonewho canhelpdefine structured, reusable ways to measure AI adoption and value across the enterprise, including standard metric definitions and value hypotheses.
Hands-on analytics and dashboarding
This is not just a consulting role. It-requiresdirect work with data, dashboard tools, KPI logic, reports, and visual storytelling.
Executive communication and data storytelling
A major requirement is turning complex metrics into clear narratives for senior leaders, while also being able to explain methods to practitioners and technical teams.
Cross-functional influence
The person willlikely needto drive alignment across business units, IT, governance, privacy, HR, and engineering without formal authority.
Business-value and ROI thinking
A candidate must be able to distinguish between usage metrics and business outcomes, and explain when value is direct, estimated, or better represented through proxies
Change/adoption measurement
Because the role sits within AI readiness and enablement,itvalues experience measuringproficiency,behaviorchange, and digital transformation outcomes
Governance- and privacy-aware judgment
Preferred experience in regulated or risk-aware environments suggests strong relevance for privacy-safe reporting, responsibleusemetrics, and collaboration with governance stakeholders.
Toolsand methods:
The roleis likely to usea practical analytics stack rather than advanced model development tools. Based on the responsibilities, likely tools/methods include:
BI/dashboard toolssuch as Power BI orDatabricks AI/BI
Data warehousing tools including Databricks
SQL and spreadsheet-based analysis
PossiblyPython or Rfor deeper analysis
Cross-platform telemetry / usage logs
Reporting feeds from AI tools, enablement systems, and business outcome systems
Qualifications:
Bachelors degree in computer science, data science, statistics, mathematics, engineering, information systems, or a related field, or equivalent experiencerequired.
Less than 2 years of experience in artificial intelligence, machine learning, data science, analytics, software development, or a related field, or equivalent experiencerequired.
Prior experience working with large data sets within an enterprise
Prior experience and knowledge with AI Readiness, Enablement, AI Adoption, Engagement and Value
Experience with Databricks highly desired
Excellent written & verbal communication skills
Exceptional organizational skillsets.
Ability to support the following:
Define common KPIstandardsso business units are not measuring AI success inconsistently.
Build dashboards, scorecards, andreportingthat show what is being adopted, where usage is growing or lagging, and whether AI is creating business value.
Analyze trends and gapsto recommend actions for enablement, governance, and investment decisions.
Partneracross matrixed stakeholdersto define meaningful success measures for specific AI initiatives.
Develop ROI/value methodsthat connect AI to measurable business outcomes such as time saved, throughput, quality gains, reduced errors, avoided risk, or cost savings.
Maintain an enterprise viewacross multiple tools and use cases, not just isolated reporting for one platform.
We provide compensation, benefits, and resources that enable a highly inclusive culture and support our team memberss ability to live with purpose every day. In addition to traditional offerings like medical, dental, and vision care, we also provide a comprehensive suite of benefits that focus on the physical, emotional, financial, and social aspects of wellness. This encompasses support for working families, which may include backup dependent care, adoption assistance, infertility coverage, family building support, behavioral health solutions, paid parental leave, and paid caregiver leave. To encourage your personal growth, we also offer a variety of training programs, professional development resources, and opportunities to participate in mentorship programs, employee resource groups, volunteer activities, and much more. For details, visit
Full timeAbout Amerisource Bergen
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