Data Analyst, Network Analytics
Overland Park, KS, United States2d ago
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Skills
About the role
What you'll do:
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Conduct advanced data analysis on complex datasets to identify trends, assess performance across campaigns, clients, and demographic segments, and deliver actionable insights
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Translate analytical findings into clear insights and recommendations that support internal stakeholders and cross-functional partners
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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
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Lead data investigations to resolve data quality issues and support business initiatives
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Partner cross-functionally with Product, Engineering, Operations, and Client Services to develop data solutions
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Use SQL, Databricks, Python, and AI tools (e.g., Claude) independently to process, analyze, and derive insights from large datasets
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Contribute to the evaluation and adoption of new technologies that advance analytics capabilities
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Maintain and contribute to data governance standards, ensuring high-quality, reliable, and compliant data assets
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Develop metrics, KPIs, and analytical frameworks to support Quest products
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Document and track project work, ensuring tasks are properly scoped and managed in systems such as DevOps
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Identify and recommend improvements to outreach strategies and data processes based on insights
What it requires:
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Bachelor’s degree in Data Analytics, Computer Science, Engineering, or a related field (or equivalent practical experience)
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3+ years of data analysis experience, preferably within healthcare, SaaS, or data-intensive environments
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Proven experience working with large, complex datasets and conducting in-depth data investigations
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Experience supporting product development, data quality initiatives, or analytics-driven business decisions
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Strong proficiency in SQL (intermediate to advanced) for data extraction, transformation, and analysis
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Hands-on experience with modern data platforms such as Databricks, Spark, or similar distributed data processing tools
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Proficiency in one or more programming languages such as Python, SQL, R, Scala, or Java
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Experience with BI and data visualization tools (e.g., Looker or similar platforms)
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Experience leveraging AI tools (e.g., Claude or similar platforms) to support data analysis, pattern recognition, anomaly detection, and workflow automation
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Ability to incorporate AI-assisted approaches into data investigations and reporting to improve efficiency and scalability
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Familiarity with emerging AI/ML concepts and their application in analytics and data quality improvement
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Strong understanding of data management best practices, including data quality, governance, and stewardship principles
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Experience defining and developing metrics, KPIs, and data models to support business and product needs
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Experience interacting with clients, vendors, and cross-functional stakeholders to understand requirements and deliver insights
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Excellent written and verbal communication skills, with the ability to present complex findings clearly
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Strong organizational skills and ability to manage multiple priorities
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Curiosity, adaptability, and a continuous learning mindset, particularly with evolving technologies and AI tools