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# Salesforce Developer

- **Company:** CareerCircle
- **Location:** Charlotte, NC, United States (Remote available)
- **Experience:** Expert
- **Salary:** $83,430.0 - $222,480.0
- **Contract:** Permanent contract
- **Skills:** Association of Accounting Technicians, Microsoft Excel, Artificial Intelligence, Data Analysis, Business Logic, Augmented Reality, BigQuery, Health Informatics, Spreadsheets, Clinical Data Management, Clinical Data Repository, Profiling, Information Systems, Data Dictionary, Information Engineering, Data Governance, Data Integrity, Data Profiling, Data Retention, Data Security, Data Systems, Data Visualization, Distributed Data Store, Google Analytics, Health Information Management, Healthcare Effectiveness Data and Information Set, Python (Programming Language), Machine Learning, Metadata, Microsoft Office, Microsoft PowerPoint, Reference Data, Power BI, Software Engineering, SQL Databases, Switch Virtual Interface, Tableau (Software), Feature Store, Google Cloud, Cloud Platform System, GitHub Copilot, Fast Healthcare Interoperability Resources, System Availability, Virtual Reality, Information Technology, Data Lineage, Health Level Seven International, Data Management, Tools for Reporting, Data Pipelines, Powerapps, Mixed Reality
- **Published:** October 8, 2026
- **Apply:** https://www.careercircle.com/jobs/all/all/usa/all/all/ae76f21f-53b6-4243-8952-d092e8bbb1e5

## About the Role

* 4+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.

 * Expertise in clinical data types and structures, including CCD data, lab results, clinical notes, and administrative healthcare data.

 * Strong knowledge of clinical coding systems and terminologies, such as ICD-10, CPT, HCPCS, SNOMED-CT, LOINC, NDC, and RxNorm.

 * Experience designing and documenting data models, taxonomies, or classification frameworks for clinical or healthcare data.

 * Proven ability to enable and support downstream data consumers (analysts, data scientists, business users) through documentation, training, and consultative support.

 * Proficiency with SQL and experience working with large-scale healthcare datasets.

 * Experience using cloud-based data platforms, preferably Google Cloud Platform (GCP) tools including BigQuery, for querying, transforming, and managing data.

 * Strong understanding of data quality principles, including validation, profiling, and monitoring of healthcare data.

 * Excellent written and verbal communication skills, including the ability to explain complex clinical data concepts to both technical and non-technical audiences.

Preferred Qualifications

 * Proven experience integrating clinical (CCD/OMOP/FHIR) and administrative (claims) data into unified, patient-centric data models, with deep understanding of the strengths, limitations, and complementary nature of each data type.

 * Experience with patient data normalization & standardization for patient attributes and cross source harmonization.

 * Hands-on experience reconciling clinical and claims data, including diagnosis alignment, medication reconciliation (prescribed vs. dispensed), and encounter/visit matching.

 * Experience integrating third-party and enrichment data sources, including SDOH indices (ADI, SVI), consumer/demographic data, mortality data, and provider reference data into patient-level datasets.

 * Expert knowledge of clinical and administrative coding systems, including ICD-10-CM/PCS, CPT/HCPCS, SNOMED-CT, RxNorm, NDC, LOINC, and NPI.

 * Experience with classification and grouping systems such as HCC, CCS, DRG, and therapeutic class hierarchies.

 * Experience designing patient-centric data models, feature stores, and dashboards that aggregate longitudinal data across sources, including demographics, encounters, conditions, medications, labs, utilization, cost, and enrichment attributes

 * Proven ability to enable downstream data consumers through analytics and well-documented, validated, and reusable data assets, with experience creating data dictionaries, lineage documentation, and self-service analytics layers.

 * Understanding of healthcare business contexts such as care management, value-based care, quality measurement (HEDIS, Stars), and population health.

Education

 * Bachelor's degree in health informatics, Public Health, Nursing, Health Information Management, Computer Science, Statistics, or a related quantitative or clinical field-or an equivalent combination of formal education and experience.

 * Master's degree or higher in Health Informatics, Biomedical Informatics, Clinical Informatics, Public Health, Epidemiology, or a related field is strongly preferred.

 * Clinical background (RN, PharmD, MD, or similar) with transition into informatics/analytics is highly valued., Curiosity
Economics
Operations
Leadership
Automation
Governance
Statistics
Positivity
Mathematics
Scalability
Forecasting
Communication
Data Analysis
Investigation
Accountability
Quick Learning
GitHub Copilot
Detail Oriented
Microsoft Excel
Problem Solving
Reporting Tools
Business Process
Computer Science
Operational Risk
Data Engineering
Strong Work Ethic
Solutions Support
Business Valuation
Production Process
Financial Services
Workflow Management
Root Cause Analysis
Information Systems
Operations Research
Microsoft PowerPoint
Software Development
Organizational Skills
Business Requirements
Full Stack Development
Business Transformation
Financial Stress Testing
SQL (Programming Language)
Python (Programming Language)
Continuous Improvement Process
Troubleshooting (Problem Solving)
Tableau (Business Intelligence Software)
+0

Google Data Analytics

## Description

BigQuery
Taxonomy
Dashboard
Statistics
Compassion
Demography
CPT Coding
Data Types
Informatics
Data Quality
Epidemiology
Data Science
Data Privacy
Presentations
Data Modeling
Public Health
Data Integrity
Business Logic
Medical Coding
Data Pipelines
Reference Data
Medical Records
Data Governance
Data Dictionary
Care Management
Computer Science
Machine Learning
Data Engineering
Value-Based Care
Data Availability
Anomaly Detection
Population Health
Advanced Analytics
Data Visualization
Health Informatics
Longitudinal Study
Data Documentation
Time Off Management
Clinical Informatics
Healthcare Analytics
Public Health Nursing
Clinical Documentation
Biomedical Informatics
Artificial Intelligence
Clinical Data Warehouse
Clinical Data Management
National Drug Code (NDC)
Switch Virtual Interface
Self Service Technologies
ICD Coding (ICD-9/ICD-10)
Medication Reconciliation
SQL (Programming Language)
Program Process Monitoring
Verbal Communication Skills
Google Cloud Platform (GCP)
Health Information Management
Certified Coding Specialist (CCS)
Systematized Nomenclature Of Medicine
Healthcare Common Procedure Coding Systems
Fast Healthcare Interoperability Resources (FHIR)
Logical Observation Identifiers Names And Codes (LOINC)
HEDIS (Healthcare Effectiveness Data And Information Set)
Health Insurance Portability And Accountability Act (HIPAA) Compliance, CVS Health's Analytics & Behavior Change (A&BC) team is an organization working to solve some of the most challenging problems at the intersection of technology and healthcare. A&BC leverages advanced analytics, clinical informatics, and hypothesis-driven approaches to transform data into actionable, customer-centric insights that drive growth, improve health outcomes, and expand access to healthcare across all CVS Health businesses. Our teams build next-generation data and AI products that help power CVS Health to make healthier happen for 100+ million customers.

The A&BC organization is looking to grow its Clinical Data Science & AI team. Join us as we embark on an exciting journey to drive a transformational shift in how CVS Health leverages clinical data and analytics to become the leader in consumer healthcare in the U.S.

As a Senior Data Scientist - Clinical Informatics (Analytics Enablement), you are tasked with activating CVS Health's clinical data repository to improve outcomes across multiple lines of business and use cases. You will serve as a bridge between clinical data assets and the analysts, data scientists, and business partners who consume them-ensuring data is accessible, well-documented, fit for purpose, and aligned with clinical and regulatory standards.

You will:

 * Serve as a subject matter expert in clinical data, including CCD data, claims, pharmacy, lab results, and clinical documentation, with deep understanding of how to structure and apply this data to solve healthcare problems.

 * Design and maintain clinical data models, taxonomies, and classification frameworks that enable consistent interpretation and use of clinical data across the organization.

 * Build the clinical data feature store, establishing standards, documentation, and best practices that accelerate adoption of clinical data for downstream analytics, reporting, and AI/ML use cases.

 * Develop analytics by building well-documented, validated, and reusable data assets (tables, views, features) that empower analysts and data scientists to work independently with clinical data.

 * Create and maintain comprehensive data documentation, including data dictionaries, lineage, business logic, known limitations, and appropriate use guidelines for clinical datasets.

 * Build queries, dashboards, and data visualizations to effectively communicate data quality metrics, data availability, and clinical insights to technical and non-technical stakeholders.

 * Partner with clinical, operational, and business stakeholders to understand their data needs, translate requirements into data solutions, and ensure clinical data assets meet their analytical objectives.

 * Maintain data quality frameworks for clinical data, including validation rules, anomaly detection, and monitoring processes to ensure data integrity and reliability.

 * Translate clinical concepts into analytical frameworks, ensuring that business partners understand the capabilities and limitations of available clinical data.

 * Collaborate with data engineering teams to inform data pipeline development, ensuring clinical data is ingested, transformed, and stored in ways that support downstream analytics needs.

 * Contribute to data governance initiatives, including compliance with HIPAA, data privacy regulations, and internal data stewardship policies.

 * Develop and deliver training, presentations, and consultations to existing and prospective data consumers on clinical data assets, appropriate use, and analytics opportunities.

 * Stay current with clinical data standards (HL7, FHIR, ICD-10, SNOMED-CT, LOINC, CPT, NDC, RxNorm) and industry best practices in clinical informatics., Auditing
Metadata
Dashboard
Operations
Leadership
Management
Governance
Innovation
Data Access
Coordinating
Communication
Mixed Reality
Data Pipelines
Data Retention
Creative Teams
Detail Oriented
Problem Solving
Data Governance
Virtual Reality
Technical Issues
Data Sovereignty
Augmented Reality
Business Valuation
Product Engineering
Reporting Solutions
Software Engineering
Full Stack Development
Business Transformation
Verbal Communication Skills
Business Continuity Planning
Troubleshooting (Problem Solving)
+0

Google Data Analytics

Google IT Automation with Python
Sr. Data Analyst
Leidos

Washington, DC*Remote

Surveys
Auditing
Power BI
Equities
Dashboard
Powerapps
Leadership
Management
Market Data
Multitasking
Spreadsheets
Missing Data
Data Lineage
Communication
Data Profiling
Microsoft Excel
Data Governance
Data Dictionary
Microsoft Office
Business Metrics
Performance Metric
Financial Modeling
Aviation Technology
Organizational Skills
Distributed Data Store
Public Trust Clearance
SQL (Programming Language)
Unmanned Aerial Systems (UAS)
National Airspace System (NAS)
Federal Aviation Administration
Key Performance Indicators (KPIs)
Association of Accounting Technicians
Tableau (Business Intelligence Software)
+0
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