Data Analyst

About CertifyOS

CertifyOS is building the data infrastructure that powers modern healthcare.

Today, healthcare organizations rely on fragmented and outdated provider data. This creates unnecessary administrative work, regulatory risk, and higher costs across the system. We’re solving that problem.

Our API-first platform automates provider licensing, enrollment, credentialing, and network monitoring by connecting directly to hundreds of primary data sources. We help healthcare organizations maintain accurate, compliant, and reliable provider networks at scale.

Our vision is simple: One API. One provider ID. Frictionless provider data.

We’re backed by leading investors and built by a team with deep experience in provider data systems. At CertifyOS, we value authenticity, accountability, collaboration, results, and openness to feedback. We’re building a high-ownership team focused on solving real infrastructure problems that impact millions of patients.

ROLE OVERVIEW

We are looking for a Data Analyst to analyze large datasets, ensure data coverage, accuracy, completeness, and freshness, and drive data-driven improvements. The role involves data analysis, data readiness, quality monitoring, automation, and cross-functional collaboration to ensure reliable data delivery and successful business launches.

KEY RESPONSIBILITIES

- Data Monitoring: Monitor data freshness, coverage, pipeline failures, and operational metrics; identify issues and coordinate resolutions.

- Data Readiness: Own end-to-end data readiness activities, identify coverage gaps, and ensure data quality standards are met before go-live.

- Data Quality & Monitoring: Perform data validation, reconciliation, and quality assessments; monitor data freshness, coverage, and pipeline failures.

- Issue Resolution & Coordination: Investigate data issues, coordinate refreshes and corrective actions, and collaborate with cross-functional teams to resolve data gaps.

- Dashboards & Reporting: Build and maintain dashboards, quality scorecards, and operational reports to track key metrics.

- Automation & Improvements: Develop SQL and Python-based workflows to automate data processing, validation, reporting, and recurring analysis.

REQUIRED SKILLS

- Strong proficiency in SQL (Google BigQuery) and Python (Pandas).

- Hands-on experience with Google Cloud Platform (GCP), particularly BigQuery and Google Cloud Storage (GCS).

- Strong analytical and problem-solving skills, with the ability to identify data patterns, trends, anomalies, and root causes.

- Experience with data cleaning, preprocessing, validation, and reconciliation.

- Experience with data visualization tools such as Looker , Studio, Power BI, or Tableau.

- Strong communication skills and ability to independently manage analytical workflows.

GOOD TO HAVE

- Healthcare domain knowledge, particularly provider data, credentialing, or licensing.

- Familiarity with ETL/ELT pipelines, data ingestion, and workflow automation.