Healthcare Data Analyst: AI-Driven Insights

Quest Analytics; Clayton (NC); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Remote or hybrid or in-office options

Medical, dental and vision plans

401k Matching

Wellness benefits

Flexible vacation

Job summary

Quest Analytics seeks a highly analytical Data Analyst to join the Provider Network Analytics team. You will work with large healthcare datasets (claims, provider directories) to uncover trends and support data-driven network optimization.

You will leverage SQL, Python, Databricks, and AI tools to derive insights, ensure data quality, and translate findings into actionable recommendations for internal stakeholders across product and engineering teams.

Qualifications

• Bachelor's degree or equivalent experience in data analytics or related field.
• 3+ years data analysis experience, preferably in healthcare or data-intensive environments.
• Experience with large datasets and data investigations.

Responsibilities

• Conduct advanced data analysis on complex healthcare datasets to identify trends and insights.
• Translate findings into actionable recommendations for internal stakeholders.
• Collaborate with Product, Engineering, and Client Services to develop data solutions.
• Lead data quality initiatives and resolve data governance issues.
• Document and track project work in DevOps or similar systems.
• Develop metrics and analytics frameworks to support Quest products.

Skills

SQL

Databricks

Python

BI/Looker

AI tools (Claude)

Data governance

Data quality

Stakeholder communication

Problem solving

Cross-functional collaboration

Education

Bachelor's degree in Data Analytics / CS / Engineering

Tools

Databricks

Spark

Python

SQL

Looker

Claude AI

Job description

Quest Analytics seeks a highly analytical Data Analyst to join the Provider Network Analytics team. You will work with large healthcare datasets (claims, provider directories) to uncover trends and support data-driven network optimization.

You will leverage SQL, Python, Databricks, and AI tools to derive insights, ensure data quality, and translate findings into actionable recommendations for internal stakeholders across product and engineering teams.