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# Data Scientist

- **Company:** Cadence, Inc.
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $190,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Information Engineering, Data Structures, Data Warehousing, Query Languages, Standard Sql, Large Language Models, Snowflake, Prompt Engineering, Build Management, Core Data, Information Technology
- **Published:** September 24, 2026
- **Apply:** https://www.builtincolorado.com/job/staff-data-scientist/11342644?handler=ApplyRedirect

## About the Role

* 9+ 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 and the ability to communicate how AI-powered care models work to clinical, operational, and external partner audiences

## Description

We're hiring a Staff Data Scientist to define the KPIs, data models, and analytical infrastructure that support Cadence's product, operational, and clinical decisions for our Advanced Primary Care Management business unit. You will partner closely with product management, operations, care delivery, 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.

What You'll Do

 * Own the analytical strategy for Cadence's digital primary care program end-to-end by defining what outcomes and KPIs matter, diagnosing ambiguous operational and clinical problems, and serving as the primary thought partner to clinical and operational leadership; exploring patient vitals, EHR data, and clinician-generated data to surface insights that close care gaps, drive better outcomes, and inform program strategy.
 * Define and communicate outcome frameworks for AI-powered primary care, translating clinical and operational performance into clear, credible narratives for external partners including health systems and payers, and serving as the analytical voice in those conversations.
 * Design and build core data models in dbt from the ground up, establishing canonical metric definitions, data collection standards, and the structural foundation that the broader team relies on; maintain the modern data stack (Snowflake, Fivetran, dbt) to keep infrastructure accurate, well-documented, and built to scale.
 * Deliver advanced analytics across the full stack from pipeline construction and data engineering to predictive modeling, staffing and capacity forecasting, and revenue modeling in partnership with operations and executive leadership.
 * Build and maintain reports and dashboards that monitor growth, engagement, clinical outcomes, and Cadence's demonstrated value to patients and health system partners with metrics that are trustworthy and tied to decisions.
 * Embed AI meaningfully into the analytics function by identifying high-value use cases, building reusable workflows and automation, and leading adoption of LLM-assisted tools that reduce manual overhead and expand what the team can produce., Leads data science for AML watchlist screening, developing multilingual NLP, entity resolution, information extraction, matching, risk-scoring, and graph-based detection systems. Builds data quality pipelines, evaluation frameworks, threshold tuning, backtesting, and production ML capabilities. Partners with Product and Engineering to deploy research at scale, leads technical initiatives, mentors peers, and translates model performance into compliance and business outcomes.
Top Skills: Graph-Based MethodsHuggingface TransformersLangchainLanggraphLarge Language ModelsNamed Entity RecognitionNlpPythonPyTorchSpacySQL
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