Senior / Lead Analyst, Customer Insights

The company is dedicated to happier, healthier days for all. We believe that there is a better healthcare world – one powered by data. Our platform transforms complex, diverse data into a unified foundation for health, helping organizations deliver better care, boost revenue, and lower costs.

We’re a team of fiercely driven individuals committed to making healthcare more sustainable—and we’re looking for passionate people to help us get there.

For more information, visit the company.io.

Why This Role Is Important to the company

Analytics sits at the center of how the company 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 the company'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 the company'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 the company 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 the company'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

In 6 months

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

In 12 months

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

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 the company's core data platform (Foundry, AWS data lake environments)

• For analytics-engine placements: serve as the lead analytics strategist for at least one of the company'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 the company'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 the company's broader analytics strategy and reusable methodology — and, for some placements, an external one, representing the company'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 the companyn 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 the company'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

About the company

The company.io helps innovative providers and payers across the country transform healthcare to reduce cost while improving patient health. We do this by aggregating large amounts of disparate data, applying algorithms to identify opportunities to provide better patient care, and making those opportunities actionable by physicians at the point of care in near-real time. We are passionate about helping our customers drive meaningful outcomes. We are growing fast and have emerged as a market leader in the highly competitive population health management software market and have been recognized by industry analysts KLAS, IDC, Forrester, and Chilmark for our leadership. For a better sense of our brand and products, please explore our website.

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