Senior Business and Data Analyst

We are seeking an experienced Business and Data Analyst to join our team. In this role, you'll be the analytical engine between a client's business need and the data solution that delivers it. You'll turn business questions into precise, testable requirements, then use the data itself to prove out what's possible: profiling sources, validating assumptions, and shaping designs that are clean, buildable, and grounded in evidence rather than opinion. You'll own the requirements and analysis for your use cases and workstreams, working in close partnership with Business Solution Managers who hold the broader engagement.

Doing that well takes two things at once: command of healthcare business context, and deep, hands-on fluency in the data. This is a client-facing role. You'll translate complex healthcare challenges into rigorous requirements, and you'll use SQL and analytical judgment to show clients and delivery teams what the data actually says, where it falls short, and what that means for the design.

No engagement lives in isolation. A data model built for one client's use case can share structure with a completely different client's need; a transformation rule written for one state's requirements often anticipates the next state's. You'll learn to see each requirement as part of a larger system of clients, states, use cases, and data flows, and to flag where a design can be reused or where it could collide with other work.

Our clients are US health plans and the partners who serve them, and the engagements span everything it takes to make their data usable. That can mean standardizing and migrating data onto a new platform, meeting evolving regulatory and compliance mandates, or powering the broader analytics and reporting programs that drive payer performance across Medicare, Medicaid, and Commercial lines of business.

Analyze the Data and Build the Evidence

- 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.

Drive Requirements and Design for Your Use Cases

- 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.

Compensation for this role is based on experience, skills, and location, and includes base salary plus eligibility for performance bonuses and equity grants.

- Competitive Leave & Benefits

- Comprehensive health coverage

- Equity for every employee – share in our success

- Growth-focused environment – your development matters here

Work arrangements

- Standard hours: 9 hours/day, 5 days/week

Our Commitment as an Equal Opportunity Employer

As a mission-led technology company helping to drive better healthcare outcomes, Abacus Insights believes that the best innovation and value we can bring to our customers comes from diverse ideas, thoughts, experiences, and perspectives. Therefore, we dedicate resources to building diverse teams and providing equal employment opportunities to all applicants. Abacus prohibits discrimination and harassment regarding race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

At the heart of who we are is a commitment to continuously and intentionally building an inclusive culture—one that empowers every team member across the globe to do their best work and bring their authentic selves. We carry that same commitment into our hiring process, aiming to create an interview experience where you feel comfortable and confident showcasing your strengths. If there’s anything we can do to support that—big or small—please let us know.

AI Use in Recruitment

We use AI-powered tools throughout our recruitment process. This includes Greenhouse's Real Talent Matching Technology, which helps prioritize applications based on job-related criteria, as well as additional AI tools used to support sourcing, interview preparation, and other recruiting tasks. We do not remove the human element—our recruiters and hiring teams review all applications and make all decisions related to candidate progression and hiring, regardless of which tools are used to support that process.

Identity and Location Verification

To protect the integrity of our hiring process, all interviews are conducted by live video with your camera on. Virtual or blurred backgrounds and headsets are not permitted absent an approved accommodation, and you should be in a well-lit, private space where your face and surroundings are clearly visible. Candidates who advance may also be asked to complete identity and location verification, which may include verifying your identity, work history, and confirming that you are located where your application states. Applications containing knowingly false or materially misrepresented information, including identity, location, or credentials, may be disqualified, and any offer may be rescinded if a material misrepresentation is discovered at any point in the process.