Clinical Encounter Data Analyst US Healthcare Claims

Health Data Max provides a cloud-based clinical AI analytics platform for the US healthcare market. Our platform brings together claims, encounter files, and medical charts into a single validated foundation, and submits encounter data to CMS on behalf of health plans.

We are hiring a Clinical Encounter Data Analyst who knows US healthcare encounter data at the field level and can read a medical chart with a coder's eye. You will examine claim and encounter records to confirm that they are complete, clinically plausible, and supported by the documentation. You will work with client data extracts, 837 files, and medical records, alongside our engineering, AI, and submissions teams.

A clinical degree (pharmacy, medicine, dentistry, nursing, or equivalent) is a strong advantage.

1. Encounter data analysis and validation

• Profile and validate client claims and encounter extracts across Professional, Institutional, DME, and Dental encounter types.
• Check field-level completeness and accuracy: ICD-10-CM/PCS, CPT/HCPCS, CDT, modifiers, revenue codes, type of bill, place of service, claim frequency codes, dates of service, admission and discharge data, NPI and taxonomy, and NDC.
• Apply clinical plausibility checks, such as diagnosis against procedure, age and sex conflicts, and drug against diagnosis.
• Identify data quality issues at source and document them clearly for clients and internal teams.

2. Medical chart review and coding

• Review medical charts and assign or validate ICD-10-CM diagnosis codes against clinical documentation.
• Compare coded encounter data with the medical record and flag unsupported, missing, or conflicting diagnoses.
• Provide clinically informed review of AI-generated coding suggestions and feed findings back to the product team.

3. EDI 837 and submission support

• Map source data fields to X loops and segments (837P, 837I, 837D).
• Review outbound 837 files before submission and investigate rejections.
• Analyse acknowledgement and response files (TA1, 999, 277CA, and CMS encounter response reports) and trace errors to root cause.
• Reconcile submitted, accepted, and rejected records against source claims.

4. Documentation and collaboration

• Define and maintain data dictionaries, mapping specifications, and validation rules.
• Prepare test cases and validate platform outputs against source data.
• Support client onboarding, data mapping, and UAT.

• 3+ years working with US healthcare claims or encounter data, preferably for payers (Medicare, Medicaid, or commercial).
• Field-level knowledge of professional and institutional claims (CMS-1500 and UB-04).
• Hands-on medical chart review and ICD-10-CM coding experience.
• Working knowledge of code sets: ICD-10-CM, CPT/HCPCS, revenue codes, type of bill, and place of service.
• Good SQL and Excel skills for data profiling, reconciliation, and root‑cause analysis.
• Strong analytical and documentation skills, with excellent written and spoken English.
• Self‑directed and comfortable in a startup environment, with some overlap with US time zones.

• Clinical degree:
  
  B.Pharm / M.Pharm / Pharm.
  
  D, MBBS, BDS, BAMS, BHMS, Nursing, or equivalent.
• Hands‑on experience with EDI 837 (P/I/D) file structure.
• Exposure to DME and dental encounters, including CDT and NDC code sets.
• Coding certification: CPC, CCS, COC, or equivalent.
• Experience with CMS encounter data submissions and response reports.
• Python for data analysis; familiarity with FHIR or HL7.
• Exposure to AI/ML workflows in healthcare.