Data Analyst, Network Analytics

Your Quest: Help make a big difference in healthcare access

At Quest Analytics our team members can fulfill their quest to work in an innovative, collaborative, challenging and flexible environment supportive of personal growth every day. The team is driven to make healthcare more accessible for all Americans. We are seeking a highly analytical and technically skilled Data Analyst to join our Provider Network Analytics team.

As a Data Analyst, you will play a key role in advancing the intelligence and precision of health plan network analytics. This position focuses on working directly with large-scale healthcare datasets, including claims data, provider directory files, and provider network files, to uncover trends, measure network performance, and support the development of data-driven strategies for provider network optimization and improve network performance.

You will be responsible for identifying and quantifying network challenges, conducting deep analytical investigations, and applying structured data exploration to generate meaningful, context-rich insights. This role requires a strong command of data tools, rigorous attention to data quality, and a passion for using data and analytics to solve complex problems in healthcare delivery.

This role offers the opportunity to work on cutting-edge provider network analytics initiatives, drive efficiencies through automation, and apply critical thinking. If you are passionate about data, analytics, and problem-solving, we encourage you to apply!

What you'll do:

Conduct advanced data analysis on complex datasets to identify trends, assess performance across campaigns, clients, and demographic segments, and deliver actionable insights

Translate analytical findings into clear insights and recommendations that support internal stakeholders and cross-functional partners

Analyze healthcare provider and organizational data to resolve entity matching across multiple data sources, determine data sourcing strategies, define entity relationships and data structures, and identify opportunities to leverage data in new products and features

Lead data investigations to resolve data quality issues and support business initiatives

Partner cross-functionally with Product, Engineering, Operations, and Client Services to develop data solutions

Use SQL, Databricks, Python, and AI tools (e.g., Claude) independently to process, analyze, and derive insights from large datasets

Contribute to the evaluation and adoption of new technologies that advance analytics capabilities

Maintain and contribute to data governance standards, ensuring high-quality, reliable, and compliant data assets

Develop metrics, KPIs, and analytical frameworks to support Quest products

Document and track project work, ensuring tasks are properly scoped and managed in systems such as DevOps

Identify and recommend improvements to outreach strategies and data processes based on insights

What it requires:

Bachelor’s degree in Data Analytics, Computer Science, Engineering, or a related field (or equivalent practical experience)

3+ years of data analysis experience, preferably within healthcare, SaaS, or data-intensive environments

Proven experience working with large, complex datasets and conducting in-depth data investigations

Experience supporting product development, data quality initiatives, or analytics-driven business decisions

Strong proficiency in SQL (intermediate to advanced) for data extraction, transformation, and analysis

Hands-on experience with modern data platforms such as Databricks, Spark , or similar distributed data processing tools

Proficiency in one or more programming languages such as Python, SQL, R, Scala, or Java

Experience with BI and data visualization tools (e.g., Looker or similar platforms)

Experience leveraging AI tools (e.g., Claude or similar platforms) to support data analysis, pattern recognition, anomaly detection, and workflow automation

Ability to incorporate AI-assisted approaches into data investigations and reporting to improve efficiency and scalability

Familiarity with emerging AI/ML concepts and their application in analytics and data quality improvement

Strong understanding of data management best practices, including data quality, governance, and stewardship principles

Experience defining and developing metrics, KPIs, and data models to support business and product needs

Experience interacting with clients, vendors, and cross-functional stakeholders to understand requirements and deliver insights

Excellent written and verbal communication skills, with the ability to present complex findings clearly

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