Senior / Lead Analyst, Customer Insights

Analytics sits at the center of how Arcadia turns complex healthcare data into better outcomes and smarter decisions.

On the product side, that means building and owning the productized analytics engines — risk, medical economics, episodes-of-care, and more — that power Arcadia's platform company-wide, built once and delivered at scale across our entire customer base.

On the Customer Insights side, that means going deep on a specific customer's specific problem: custom data models, bespoke dashboards, advisory work, and long-running embedded programs that don't fit a one-size-fits-all product. We describe Customer Insights' work as sitting between a platform and a plan — more customized and hands-on than an off-the-shelf reporting product, more flexible and embedded in the customer's actual decisions than a traditional outsourced consulting engagement.

We're currently hiring for several closely related analyst roles across this broader Analytics organization — spanning ownership of one of Arcadia's core analytics engines, program-specific analytical development for a major state Medicaid risk-stratification initiative,  a ground-up registry build for a national quality organization, versatile project and retainer delivery across our health system and payer customers, and dedicated analytics support for a major national health plan's Medicaid program. All of these roles sit at the Senior Analyst or Lead Analyst level, combine technical excellence with real influence over analytic strategy and (for some placements) product direction, and shape how Arcadia and its customers use data to improve population health outcomes, reduce costs, and enable smarter healthcare decisions.

The skills and experience below are characteristic across these roles as a set — not every requirement applies to every specific seat, and we don't expect any one candidate to bring all of it. We'll work with you during the interview process to identify which role is the best fit for your background and interests.

• Ramp into your specific engagement's data model, technical stack, and stakeholder relationships — most Customer Insights engagement has real history and context to build into, not a blank slate
• Learn Arcadia's core analytics platform and toolset (QuickSight, Foundry, dbt, the AWS ecosystem) as used in your engagement
• Deliver your first piece of analytical work that demonstrates clear value to your engagement's stakeholders 

• Own meaningful pieces of delivery independently — whether that's a program's analytical development, a portfolio of retainer/project work, or a dedicated account's dashboarding and reporting
• Be a credible, independent presence in front of the customers or partners tied to your engagement
• Contribute to at least one reusable analytical asset, framework, or automation that extends beyond your immediate engagement
• Begin taking on the ongoing health of your area, not just its delivery — standing up a backlog/tech-debt process, or growing into a broader backup role alongside your engagement's primary owner, depending on placement

• Be a recognized expert in your engagement area, trusted with its most complex or ambiguous work
•  Actively identify and pursue opportunities for automation, scalability, and reuse across your work
• Have grown into deeper ownership than where you started — full backup or co-owner on an account, sole steward of a program's tech-debt and backlog, or, for analytics-engine placements, the architect shaping that engine's roadmap toward being market-leading

• Experience with dbt-based analytics engine development (e.g., risk, medical economics, episodes-of-care) and partnering with product/engineering on roadmap
• Dashboarding experience — QuickSight or a comparable BI tool
• Enough quantitative/ML fluency to build models and hand them to a Data Science team for training
• Experience with medical economics, risk algorithms, quality data, and/or episodes-of-care analytics
• Statistical or biostatistics fluency — risk-adjustment, odds-ratio, or observed-to-expected benchmarking, etc.
• Direct experience with clinical quality or accreditation registries
• Prior experience with state Medicaid programs or similar large government health programs
• Prior experience in a project-based/retainer delivery model spanning multiple customers, rather than a single dedicated account
• Experience working within a prime contractor or partner structure on shared delivery
• Experience presenting analytic capabilities externally — customer meetings, industry conferences, publications
• Python for analysis and QA; familiarity with the AWS ecosystem, Jira, and Confluence
• Experience with data governance or data-product/monetization considerations
Note: this list spans skills relevant to several different roles across the Analytics organization — we don't expect any given candidate to have all of them. Bring what you have; we'll talk through the rest during the interview process.

The opportunity to: