This role pays less than
57%
of similar roles. Most pay
$126,800–$184,787
— the shaded band above.
At the midpoint, this role pays about
$153k
versus about
$156k
for comparable roles.
Based on 240 similar postings.
Employer
About CVS Health
CVS Health is a leading American healthcare company operating retail pharmacies, pharmacy benefit management services, and a health insurance segment through Aetna, one of the nation''s largest health insurers. Industry: Healthcare & Pharmacy
CVS Health currently has
99 open roles
on FindRole.
Listed pay typically runs
$106,605–$260,590
across 96 roles with salary data.
Senior Data Scientist - Clinical Informatics (Analytics Enablement) joins the Analytics & Behavior Change team to activate clinical data repositories and improve outcomes across multiple business lines. This role serves as a bridge between clinical data assets and downstream consumers, ensuring data is accessible, well-documented, and compliant with regulatory standards. Key responsibilities include designing clinical data models and taxonomies, building a clinical data feature store, creating reusable data assets like tables and views, and maintaining comprehensive documentation such as data dictionaries and lineage. The role requires expertise in CCD data, claims, pharmacy, and lab results using SQL and Google Cloud Platform tools like BigQuery. Candidates must navigate complex coding systems including ICD-10, CPT, SNOMED-CT, LOINC, NDC, and RxNorm to solve healthcare problems by translating clinical concepts into actionable analytical frameworks for technical and non-technical stakeholders.
What does a Data Scientist earn in New York?
Median $173200 from 35 postings across 15 companies.
Design and maintain clinical data models, taxonomies, and classification frameworks to ensure consistent interpretation across the organization.
Build and manage a clinical data feature store with established standards and documentation for AI/ML use cases.
Develop validated, reusable data assets such as tables and views to empower downstream analysts and data scientists.
Create comprehensive documentation including data dictionaries, lineage, business logic, and usage guidelines for clinical datasets.
Build dashboards and visualizations to communicate data quality metrics and clinical insights to technical and non-technical stakeholders.
Translate complex clinical concepts into analytical frameworks and actionable requirements for business partners.
Maintain data quality frameworks involving validation rules, anomaly detection, and monitoring processes to ensure integrity.
Deliver training and consultations to internal teams regarding clinical data assets and available analytics opportunities.
What we're looking for
Bachelor’s degree in health informatics, Public Health, Nursing, Health Information Management, Computer Science, Statistics, or a related field.
Master's degree or higher in Health Informatics, Biomedical Informatics, Clinical Informatics, Public Health, Epidemiology, or a related field (preferred).
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 such as ICD-10, CPT, HCPCS, SNOMED-CT, LOINC, NDC, and RxNorm.
Proficiency with SQL and experience working with large-scale healthcare datasets.
Experience using cloud-based data platforms, preferably Google Cloud Platform (GCP) tools like BigQuery.
Proven ability to support downstream consumers through documentation, training, and consulting; clinical background is highly valued (preferred).
Python
IBM watsonx
SQL
Pandas
NumPy
Scikit-learn
Machine Learning
Statistical Modeling
Data Visualization
Matplotlib
Seaborn
Cognos
Git
Version Control
AWS
Azure
IBM Cloud