Analytics Architect

We are hiring an Analytics Architect to define how Xillium sees its workforce. You will not build the tooling. You will own the design and the requirements, and work with our Analytics team to bring them to life. You decide what we measure, where and how we capture it, what the reporting should show, and how the data connects back into our other systems, including the AI that we use to improve operations over time.

The role spans every department. You will hold two views at once. One is the individual journey of a person through the company, from how they are onboarded to how they perform and grow. The other is the systemic view of how our people are deployed against the larger goals of the business.

• Define what the business needs to measure about its workforce, and translate that into clear requirements for the Analytics team to build.
• Decide where and how data is captured across departments, and how it connects back into other systems.
• Design the reporting and data flows that feed our AI systems, so those systems can guide and improve operations.
• Map the individual employee journey through the company, and the systemic view of how people are deployed against company goals.
• Work across every department to keep measurement aligned with how the operation runs.
• Partner with the Analytics team through the build, and confirm that what ships matches the intent.

• The ability to turn business needs into measurement requirements and specifications a data team can execute.
• Data literacy: an understanding of data models, metric design, reporting, and system integration, enough to direct a build without doing it.
• Systems thinking across an organization, with the ability to hold both the individual and the aggregate view.
• Process mapping and structured requirements definition.
• Clear communication with technical teams and department leads.

• Process expertise, such as an industrial engineering background or other technical education.
• Experience as an analytics product owner, business analyst, or measurement and BI designer.
• Familiarity with how AI or machine learning systems consume operational data.
• Workforce, capacity, or operations analytics background.
• Exposure to healthcare operations or a regulated delivery environment.