Senior Business and Data Analyst

Abacus Insights is seeking a Senior Business and Data Analyst to connect health plan business needs with evidence-based data solutions. The role owns requirements and analysis for assigned use cases, profiles and validates healthcare data, guides design, and partners with clients and cross-functional delivery teams.

Responsibilities:

• Write and execute SQL daily to profile source data, test assumptions, quantify data quality (completeness, validity, uniqueness, consistency, timeliness), and prototype logic before it reaches the build team
• Analyze source data to establish what is actually available and reliable: field population and distributions, key integrity, duplicates, outliers, and gaps against what the business use case needs
• Reconcile and validate outputs against source systems and client-provided benchmarks (claim counts, member months, paid amounts, enrollment spans, provider rosters), investigating variances to root cause and documenting findings
• Define and document business metrics and KPIs precisely: numerator, denominator, inclusion and exclusion logic, time basis, and grain, so every consumer of the data calculates and reads them the same way
• Perform exploratory and root-cause analysis on client questions and data anomalies, and turn findings into clear, quantified recommendations for client and internal audiences
• Summarize findings through data profiling reports, analysis readouts, and visualizations that make the story clear to non-technical stakeholders
• Lead discovery sessions for your use cases, and support broader engagement-level sessions alongside the Business Solution Manager, to understand the why and what behind each use case: the business context, pain points, expected outcomes, and success criteria, rather than just the surface-level data ask
• Translate each use case into clear, testable requirements, including success criteria and non-functional requirements, and maintain traceability from business need to requirement to design to test
• Use data analysis to sharpen and challenge requirements: confirm that what the client is asking for is supported by the data they have, and surface gaps early
• Document source-to-target mappings, transformation logic, and business rules that developers can build from, and define the test conditions and expected results QA will use to validate them
• Recommend the appropriate grain and structure of a dataset given the business context, and analyze how that grain decision ripples into the downstream reports, models, or programs that consume the data
• Identify dependencies before a design is finalized: which other workstreams, reports, or client use cases touch this same data, and how a change here could break or benefit them, escalating cross-workstream impacts to the Business Solution Manager
• Apply systems thinking: recognize when a design built for one client, state, or use case can become a reusable pattern, and raise and shape that reuse rather than discovering it in hindsight
• Drive requirements-gathering and clarification conversations with client SMEs for your use cases, since incomplete or poorly elicited requirements undermine everything built downstream
• Present analysis results, data quality findings, and recommendations to client stakeholders with clarity and confidence, and guide decisions with evidence
• Represent client intent for your use cases through delivery and serve as a day-to-day point of contact, with the Business Solution Manager owning the overall client relationship
• Translate fluently between business and technical audiences, so both sides share the same understanding
• Connect the client and the internal team on your workstreams, holding the business context, data findings, and design drivers that shape the build
• Act as the business and data analysis SME for Solution Architects, Product, QA, Account Management, and Program Management, giving them clean hand-offs with the context, business rules, and analysis they need to execute without rework or reinterpretation
• Support QA and UAT by supplying validation queries, expected results, and variance analysis, and by helping triage defects to business rule, mapping, or source data causes
• Maintain awareness of the wider engagement: understand how a decision made for one workstream affects the others, and flag those ripple effects before they surface as rework

Requirements:

• Bachelor's degree, or equivalent relevant experience
• 5+ years working in the US healthcare domain and with healthcare data (claims, provider, membership/eligibility, benefits, prior authorization, or PBM)
• Payer experience required: direct experience working with or for a US health plan (Medicare, Medicaid, or Commercial), whether in-house or through healthcare consulting
• Working command of core payer concepts such as membership/enrollment, provider, claims, and authorizations, enough to reason about business context rather than specialize narrowly in any one area
• Strong, hands-on SQL: comfortable with joins across large, multi-table datasets, window functions, CTEs, aggregations, and date/span logic, used regularly to profile, validate, reconcile, and analyze data
• Demonstrated analytical rigor: a track record of profiling data, assessing data quality, investigating anomalies to root cause, and communicating quantified findings that drove a decision
• Experience defining metrics, mentoring junior analysts, and eliciting and authoring business requirements in complex, data-driven environments
• Confident client-facing communication; able to drive a conversation, elicit requirements clearly, and present analytical findings to technical and non-technical audiences
• Comfort operating with ambiguity and re-prioritizing frequently while managing multiple use cases within a larger engagement
• Developing systems thinking: experience designing for reuse and scale across states, clients, or use cases rather than solving each case in isolation, and the ability to trace how a requirement or data model decision affects other parts of a larger data ecosystem
• Exposure to Databricks or Snowflake is desirable
• Background that already blends business analysis with hands-on data work, such as a Business Analyst, Data Analyst, or Business Data Analyst role, with exposure to client-facing delivery
• Experience with BI and visualization tools (e.g., Tableau, Power BI, or similar) to communicate analysis
• Familiarity with HEDIS and Stars quality reporting, risk adjustment, payment integrity, value-based care analytics, provider data management, or CMS interoperability (CMS-0057)
• Working knowledge of data modeling concepts, including how the grain and structure of a dataset shape its downstream use
• Familiarity with Python or similar for analysis and automation
• Familiarity with Medicaid data or PBM platforms