Provider Analytics Team Lead

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.

As the Team Lead of Provider Analytics, you’ll play a critical role in ensuring our provider data is accurate, trusted, and ready to support key business decisions. In this role, you will lead and mentor a team while remaining hands‑on with complex provider identity, network, and affiliation work. You will partner closely with stakeholders across the organization to turn ambiguous healthcare data into scalable, automated solutions that improve how we operate and make decisions.

• Lead and support a team of Analysts by providing technical direction, reviewing analytical deliverables, modeling best practices, and offering thoughtful, patient guidance on processes and problem‑solving approaches.
• Lead the identification and delivery of automation initiatives by the team, driving reusable and standardized analytical solutions that reduce manual effort and improve data reliability.
• Serve as a subject matter expert in provider data, leading complex analyses to establish accurate provider identity, network status, affiliations, and hierarchy across disparate data sources.
• Anticipate, diagnose, and resolve systemic provider data quality issues (e.g., NPI mismatches, network data delivery issues, taxonomy drift, stale affiliations), while continuously monitoring data integrity and performance trends.
• Design, develop, and maintain scalable, production‑grade SQL, Python, and Databricks workflows that support provider analytics at enterprise scale.
• Review, optimize, and provide technical guidance on analytical code produced by the team to ensure performance, reliability, consistency, and adherence to established best practices.
• Translate ambiguous business and client questions into clear analytical approaches and guide the team in producing validated outputs and actionable recommendations.
• Partner cross‑functionally with Data Engineering, Product, Web Development, and client‑facing teams to design analytics solutions, resolve complex ad hoc cases, and support strategic initiatives.
• Establish and uphold analytical standards, documentation, and validation practices to ensure long‑term reliability, auditability, and usability of provider data assets.
• Demonstrate strong ownership, communication, and accountability while independently leading complex analytical initiatives.

• Bachelor’s degree in a quantitative field (e.g., Statistics, Mathematics, Engineering, Computer Science, Finance, or Economics) or equivalent professional experience.
• 5+ years of data analysis experience, including significant hands‑on work with healthcare data (provider, claims, eligibility, or related domains).
• 2+ years of experience leading analytical work or small teams, including setting expectations, reviewing deliverables, and supporting day‑to‑day execution.
• Strong ownership, communication, and accountability while leading complex analytical initiatives directly and through a team, ensuring high‑quality execution and timely delivery.
• Proven track record of identifying root causes, driving durable solutions, and maintaining exceptional attention to data accuracy, validation, and quality.
• Highly organized and self‑motivated, with the ability to manage multiple priorities independently while collaborating effectively with others.
• Advanced SQL proficiency for querying and transforming large, complex datasets, including writing optimized, production‑ready queries and reviewing…