Data Lead - APCM

We're hiring a Data Analytics Lead to define the KPIs, data models, and analytical infrastructure that support Cadence's clinical, operational, and product decisions. You will partner closely with product management, care delivery, operations, and customer success to build a scalable analytics roadmap and translate complex data - including patient vitals, EHR records, and clinical outcomes - into insights that drive strategy. This role sits at the center of how Cadence measures and improves care delivery at scale.

• →Define and maintain the analytics roadmap in partnership with product, operations, care delivery, and customer success teams - organizing and prioritizing analytical work to provide fast, scalable support across the business.
• →Build and maintain reports and dashboards with actionable metrics that monitor growth, engagement, clinical outcomes, and Cadence's demonstrated value to patients and health system partners.
• →Explore patient vitals, EHR data, and clinician-generated data to surface insights that benefit clinical care, inform product strategy, and support care gap closure across Cadence's patient population.
• →Build models for revenue and staffing in partnership with operations leaders, and develop analyses that support strategic decision-making at the executive level.
• →Collaborate with internal stakeholders to identify data needs, define what data should be collected, and ensure metrics are consistently defined and reliable across teams.
• →Own and evolve Cadence's modern data stack - including Snowflake, Fivetran, dbt, and connected tooling - maintaining data infrastructure that is accurate, well-documented, and built to scale.
• →Build reusable analytical workflows and automation that reduce manual overhead, accelerate insight generation, and raise the quality and consistency of outputs across the analytics function.

• 5+ years of experience working with SQL or other data querying languages, with hands-on experience building and maintaining analytics, reporting, and dashboarding solutions.
• Proficiency with modern data stack tools such as Snowflake, Fivetran, and dbt, or equivalent technologies.
• Bachelor's degree in Mathematics, Statistics, Economics, Computer Science, or a related quantitative field, or equivalent practical experience.
• Practical knowledge of statistics and data analysis techniques, with the ability to translate findings clearly for both technical and non-technical stakeholders.
• Experience working with clinical or health data - including patient vitals, EHR records, or outcomes data - and familiarity with the data structures and sensitivity considerations that come with it.
• Fluency with LLM APIs, prompt engineering, and AI-assisted development tools; demonstrated experience building or evaluating AI-powered systems in production.