Senior Healthcare Data Analyst at Machinify

Job description

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. About the Role Machinify is rebuilding how health plans audit and pay claims — at scale, with AI. As a Senior Healthcare Data Analyst you will sit at the intersection of domain expertise and data engineering: translating raw claims feeds into trusted canonical models, driving payment integrity insights, and serving as the internal expert on how claims flow through adjudication. This role is for someone who knows healthcare data cold and is excited to pair that knowledge with modern AI tooling to move faster and build smarter. What You'll Do Claims mapping & transformation — Design and implement data transformations that convert raw medical and institutional claims (837 EDI, UB-04, CMS-1500) into Machinify's canonical models, applying healthcare coding standards (ICD-10-CM/PCS, CPT, HCPCS) throughout. Data quality & pipeline validation — Perform detailed audits to detect, troubleshoot, and resolve issues impacting accuracy and completeness; write SQL and Spark SQL queries to validate pipeline output end-to-end. Platform expertise — Develop deep working knowledge of Machinify's platform—from data ingestion through claims adjudication—so that analytical solutions are accurate, traceable, and business-aligned. Payment integrity — Identify overpayment patterns, COB issues, and billing edit opportunities by applying expertise in payer policy, CMS regulations, and provider reimbursement methodologies. AI-assisted workflows — Actively drive AI adoption: prompt and iterate with LLMs to accelerate analysis, identify manual processes ripe for automation, and contribute to AI-assisted pipeline development. Client onboarding — Support onboarding of new client data feeds, ensuring smooth integration with minimal disruption and clear documentation of transformation logic and lineage. Cross-functional partnership — Partner with data engineers, data science, clinical staff, and product managers to translate complex healthcare requirements into scalable data solutions; collaborate with data scientists to enable advanced analytics and ML use cases. Subject matter leadership — Serve as the go-to SME on claims coding, adjudication rules, and payer policy—mentoring analysts and engineers and advising stakeholders on risk, trends, and business impact. What You'll Bring Bachelor's degree in Business, Computer Science, Health Informatics, or a related field. 5+ years working directly with healthcare claims data — 837 EDI, encounter data, medical billing — ideally at a health plan, payment integrity vendor, or healthcare analytics firm. Deep knowledge of claim types (professional and institutional), coding systems (ICD-10-CM/PCS, CPT, HCPCS), and standard form formats (UB-04, CMS-1500). Hands-on payment integrity experience: overpayment detection, COB, billing edits, or claim editing logic. Familiarity with CMS regulations and commercial payer guidelines as they apply to claims adjudication and payment policy. Advanced SQL proficiency; comfortable writing complex analytical queries against large datasets. Solid understanding of data modeling concepts and best practices for analytics. Strong communicator — able to discuss healthcare process and payment logic directly with health plan clients, clinicians, and non-technical stakeholders. Self-starter with strong ownership, accountability, and the ability to manage multiple concurrent initiatives. Preferred Working knowledge of provider reimbursement methodologies — MS-DRG/APR-DRG pricing, fee schedules, per diem, and capitation. Proficiency with Spark SQL or a comparable distributed query engine for large-scale data environments. Exposure to ETL/ELT pipeline development or close collaboration with data engineers on pipeline design. Exposure to value-based care arrangements or risk adjustment (HCC coding, RADV). What We Offer Work from anywhere in the US! Machinify is digital-first. Full Medical/Dental/Vision for employees & their families Flexible and trusting environment where you’ll feel empowered to do your best work Unlimited FTO Competitive salary, equity, 401(k) including employer match The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks. The base salary range for this role is $140,000 - $170,000 plus private equity. Equal Employment Opportunity at Machinify We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity workplace. Machinify is an employment at will employer. We participate in E-Verify as required by applicable law. In accordance with applicable state laws, we do not inquire about salary history during the recruitment process. If you require a reasonable accommodation to complete any part of the application or recruitment process, please let our recruiters know. See our Candidate Privacy Notice at: machinify.com

Requirements

Must-haves

Data quality & pipeline validation — Perform detailed audits to detect, troubleshoot, and resolve issues impacting accuracy and completeness; write SQL and Spark SQL queries to validate pipeline output end-to-end.
Platform expertise — Develop deep working knowledge of Machinify's platform—from data ingestion through claims adjudication—so that analytical solutions are accurate, traceable, and business-aligned.
Payment integrity — Identify overpayment patterns, COB issues, and billing edit opportunities by applying expertise in payer policy, CMS regulations, and provider reimbursement methodologies.
AI-assisted workflows — Actively drive AI adoption: prompt and iterate with LLMs to accelerate analysis, identify manual processes ripe for automation, and contribute to AI-assisted pipeline development.
Client onboarding — Support onboarding of new client data feeds, ensuring smooth integration with minimal disruption and clear documentation of transformation logic and lineage.
Subject matter leadership — Serve as the go-to SME on claims coding, adjudication rules, and payer policy—mentoring analysts and engineers and advising stakeholders on risk, trends, and business impact.
Bachelor's degree in Business, Computer Science, Health Informatics, or a related field.
5+ years working directly with healthcare claims data — 837 EDI, encounter data, medical billing — ideally at a health plan, payment integrity vendor, or healthcare analytics firm.
Deep knowledge of claim types (professional and institutional), coding systems (ICD-10-CM/PCS, CPT, HCPCS), and standard form formats (UB-04, CMS-1500).
Hands-on payment integrity experience: overpayment detection, COB, billing edits, or claim editing logic.
Familiarity with CMS regulations and commercial payer guidelines as they apply to claims adjudication and payment policy.
Advanced SQL proficiency; comfortable writing complex analytical queries against large datasets.
Solid understanding of data modeling concepts and best practices for analytics.
Strong communicator — able to discuss healthcare process and payment logic directly with health plan clients, clinicians, and non-technical stakeholders.
Self-starter with strong ownership, accountability, and the ability to manage multiple concurrent initiatives.

Nice-to-haves

Working knowledge of provider reimbursement methodologies — MS-DRG/APR-DRG pricing, fee schedules, per diem, and capitation.
Proficiency with Spark SQL or a comparable distributed query engine for large-scale data environments.
Exposure to ETL/ELT pipeline development or close collaboration with data engineers on pipeline design.
Exposure to value-based care arrangements or risk adjustment (HCC coding, RADV).

Application prep

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Benefits

Benefits detected in the listing.

Dental

Vision

401(K)