Chromatography Data Analyst Pace Analytical Life Sciences
- $21–$23 Per Hour
| Location | Eden Prairie, MN (Remote) |
Role Type: Senior Data Analyst
Duration: 5 months
Location: U.S.-based; candidates must be available for meetings between 8:00 a.m. and 5:00 p.m. Eastern Time.
We are seeking a Senior Data Analyst to support the development of a Claims Reconciliation Hub. This role will focus on defining and analyzing matching criteria between pre-service member- and provider-facing cost estimates and actual medical claims submitted and adjudicated across multiple lines of business.
The ideal candidate brings extensive healthcare claims data experience, strong Snowflake and data warehousing capabilities, and a working knowledge of health plan claims processing. This individual will partner closely with business analytics stakeholders to identify relevant data sources, interpret complex claims data elements, trace claim activity through the adjudication lifecycle, and uncover patterns that support accurate estimate-to-claim matching.
Support the Reconciliation Hub initiative by defining matching criteria between pre-service estimates and final adjudicated medical claims.
Analyze claims data across major healthcare platforms to identify patterns, relationships, and reconciliation opportunities.
Trace claims from initial receipt and pre-adjudication through final adjudication, payment, and reporting.
Partner with business analytics teams to identify the appropriate data tables, attributes, identifiers, and source-system relationships needed for reconciliation analysis.
Explain and document how key membership, provider, benefit, pricing, and claims-processing data elements should be interpreted and applied.
Analyze claim changes occurring throughout the processing lifecycle, including edits, benefit determination, prior authorization matching, documentation requests, contract-based pricing, accumulators, and payment batching.
Develop insights that improve the ability to match member- and provider-facing estimates with actual submitted and adjudicated claims.
Perform data exploration and analysis using Snowflake and enterprise healthcare data warehouse assets.
Document data logic, source-to-target relationships, matching rules, assumptions, findings, and identified data gaps.
Communicate complex analytical findings clearly to technical and nontechnical stakeholders.
Support reconciliation design across multiple lines of business and healthcare claims platforms.
5+ years of experience as a Data Analyst supporting data warehousing, enterprise data, and healthcare data initiatives.
3+ years of internal experience analyzing healthcare claims data and core healthcare data assets, including enterprise data warehouse environments such as UDW.
Experience working with healthcare claims platforms, including CSP Facets, UNET, COSMOS, and USP.
Strong understanding of medical claims coding, billing, processing, adjudication, and payment workflows.
Familiarity with member, subscriber, provider, and plan identifiers and their use across claims data.
Knowledge of core claims processing capabilities, including:
Benefit determination
Claims editing
Prior authorization matching
Documentation or medical-record requests
Contract-based pricing
Deductible and out-of-pocket accumulators
Payment and batching processes
Experience using Snowflake for data analysis, data exploration, and querying healthcare data.
Strong analytical and problem-solving skills, with the ability to identify patterns across complex claims-processing data.
Excellent communication, collaboration, and stakeholder-management skills.
Ability to work independently and effectively in a fast-paced, dynamic project environment.
Must be U.S.-based and available for meetings between 8:00 a.m. and 5:00 p.m. ET.
Experience using AI/ML tools, models, or analytical techniques to support data analysis, pattern identification, reconciliation, or healthcare analytics.
Experience supporting healthcare cost-estimation, price-transparency, member financial responsibility, or claims reconciliation initiatives.
Experience designing or documenting data-matching logic, reconciliation rules, or cross-platform data lineage.



