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.

What Success Looks Like

In 3 months

• 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 

What You'll Be Doing

Technical Analytical Delivery

Translate ambiguous or partially-scoped business and clinical questions into a concrete, buildable data plan, then build the underlying data model, code, and analysis on top of it

Develop and maintain analytical pipelines and reusable data assets using SQL, dbt, and Arcadia's core data platform (Foundry, AWS data lake environments)

For analytics-engine placements: serve as the lead analytics strategist for at least one of Arcadia's productized analytics engines (e.g., risk, medical economics, episodes-of-care), owning it end-to-end while contributing to others

For engagements involving predictive or risk models: design and build the models, partnering with a dedicated Data Science team on training and validation — a consultative relationship, not a daily modeling partnership

 Build dashboards, provider scorecards, registries, self-service reporting tools, benchmarking views, and other analytical deliverables (QuickSight and beyond) on top of that modeling work, as the engagement calls for it

Maintain the analytical integrity and quality of your work, flagging issues before they reach a customer or partner; for senior placements, oversee analytic quality standards and rigor across engagements more broadly, not just your own

Program and Project Management

Manage delivery — whether that's a single program's delivery calendar and decision log, or a portfolio of concurrent projects across multiple customers — surfacing risks and tradeoffs before they become blocking issues

Create client-facing materials — status decks, decision memos, technical explainers — tailored to a range of stakeholders, from highly technical counterparts to policy or business stakeholders with limited technical background

 Delegate routine or repeatable work to junior analysts as your engagement grows, and help cross-train others for coverage

Lead cross-functional analytic initiatives that span multiple teams or engagements

Customer and Cross-Functional Partnership

Serve as a primary or supporting day-to-day contact for your engagement's customers or delivery partners, navigating scope and timeline conversations directly

Partner with Customer Management, Growth, Product, Technical Operations, and/or Engineering — depending on placement — on account strategy, product direction, or analytics roadmap; for analytics-engine placements, partner closely with product and engineering to deliver Arcadia's analytics roadmap and contribute directly to product innovation

Hold real authority at the boundaries where your work meets someone else's — able to require rework or hold a handoff that isn't ready (e.g., with a partner Data Science team), or push back on what's actually worth building with Customer Management, Growth, or Product, rather than defaulting to whatever's asked

Act as an internal thought leader on your area of expertise, contributing to Arcadia's broader analytics strategy and reusable methodology — and, for some placements, an external one, representing Arcadia's analytic capabilities at customer meetings, industry conferences, and in publications

Team Contribution

Mentor and develop junior analysts, building organizational capacity beyond your own individual delivery

Take ownership of your area's long-term health, not just its immediate delivery — a backlog/tech-debt log, a growing backup role on an account, or a roadmap for an analytics engine, depending on placement

Apply AI tooling as a standard part of your workflow — analysis, QA, documentation — not an occasional accelerant

Identify opportunities for automation, scalability, and reusability in analytical delivery, and help build those improvements out

What You'll Bring

Strong SQL and data modeling expertise — able to translate ambiguous business or clinical requirements into a concrete data plan, then build the underlying code and analysis on top of it

Healthcare data experience — claims and/or clinical data, with value-based care familiarity

Direct customer- or partner-facing experience — comfortable scoping and presenting without close oversight

Comfortable adopting AI tooling as a standard part of an analytical workflow

For Lead-level placement: demonstrated experience leading analytical work independently, managing multiple stakeholders, and mentoring less experienced analysts

Note: our experience bar across these roles generally skews toward Lead-level expectations, even for some Senior Analyst placements — but not every skill listed here or below applies to every specific seat.

Would Love For You To Have

• 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.

What You'll Get

• Become a member of the talented, energized, diverse and purpose-driven Arcadian Community with decades of collective experience in population health, product development, and data science
• Employee driven programs and initiatives for personal and professional development
• A flexible, remote-friendly company with personality and heart
• Competitive compensation and strong benefits, including Flexible Time Off

The opportunity to:

• Own real, high-stakes analytical work across some of Arcadia's most complex customer relationships and highest-visibility internal analytics products
• Work across a genuinely varied set of problems — deep technical program ownership, versatile multi-account delivery, or company-wide analytics engines, depending on placement
• Build models and analytical assets that directly shape care and coverage decisions for the members and patients they serve
 
 

Senior Analyst: $125,000 – $145,000 a year

Lead Analyst: $145,000 – $170,000 a year