Healthcare Data Scientist – Claims, Quality, & Provider Performance

Vālenz® Health is the platform to simplify healthcare – the destination for employers, payers, providers and members to reduce costs, improve quality, and elevate the healthcare experience. The Valenz mindset and culture of innovation combine to create a distinctly different approach to an inefficient, uninspired health system. With fully integrated solutions, Valenz engages early and often to execute across the entire patient journey – from care navigation and management to payment integrity, plan performance and provider verification. With a 99% client retention rate, we elevate expectations to a new level of efficiency, effectiveness and transparency where smarter, better, faster healthcare is possible.

About This Opportunity: As a Healthcare Data Scientist at Valenz, you’ll work hands-on with large, complex healthcare claims and provider datasets to ensure data accuracy and integrity. You’ll continuously dig into the data, investigate anomalies, and contribute to models that inform how we evaluate provider performance, care quality, and risk.

Using SQL and Python, you’ll identify and resolve data issues, apply statistical methods, and deliver clear, actionable insights to support smarter decision-making across the organization. This is a highly analytical and collaborative role with real impact on how care is measured, delivered, and improved.

Things You’ll Do Here:

• Utilize reference data sources and advanced validation techniques to ensure accuracy, completeness, and integrity of healthcare claims data.
• Assess provider scoring methodologies, identify discrepancies, and develop insights to optimize coverage accuracy.
• Design, develop, and maintain retrospective models for historical performance analysis, and predictive models to identify high-risk patients and prioritize actionable interventions.
• Translate complex analytical findings into clear, actionable insights, and effectively communicate results and recommendations to internal stakeholders and external clients.
• Aggregate and reconcile multiple data sources, applying statistical and computational methods to verify data integrity, identify anomalies, and implement necessary corrections.
• Execute comprehensive data analysis workflows, evaluate outcomes, and implement enhancements to improve model accuracy and data reliability.
• Review and optimize claim-matching processes, troubleshoot inconsistencies, and resolve data discrepancies to maintain high-quality outputs.
• Investigate data quality issues, conduct root cause analysis, document findings, and deliver actionable recommendations for process improvements.
• Collaborate with cross-functional teams to enhance analytical tools, refine methodologies, and implement scalable solutions that improve efficiency and analytical capabilities

• Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Engineering, Computer Science, Finance, or Economics).
• 7+ or more years of experience analyzing healthcare claims data, including complex and imperfect datasets.
• Strong analytical, problem-solving, and critical-thinking skills with proven ability to uncover root causes
• Proficiency in SQL for querying and manipulating data; familiarity with Python or similar data tools preferred.
• Advanced Excel skills, including PivotTables and complex formulas, for data modeling and reporting. ·
• Knowledge of healthcare network rosters, provider data, and quality measurement methodologies.
• Exceptional attention to detail with a commitment to accuracy, data validation, and quality assurance.
• Highly organized and self-motivated, with the ability to manage multiple priorities independently while collaborating effectively with others.

• Master’s degree

• Work Environment: You’ll need a quiet workspace that is free from distractions.
• Technology: Reliable internet connection—if you can use streaming services, you’re good to go!
• Security: Adherence to company security protocols, including the use of VPNs, secure passwords, and company-approved devices/software.
• Location: You must be US based, in a location where you c