Senior Data Scientist, Clinical Informatics (Analytics Enablement)

CVS Health

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
NYIDVTGATX
Salary
$83,430–$222,480 / yr
Posted
8 days ago
Freshness
Confirmed live yesterday
Closes
Dec 4, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $153k
This role $153k
$67k most similar roles pay here $239k

This role pays less than 55% of similar roles. Most pay $126,800–$180,125 — the shaded band above. At the midpoint, this role pays about $153k versus about $153k 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 88 open roles on FindRole.

Listed pay typically runs $118,450–$284,280 across 84 roles with salary data.

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View all roles at CVS Health

At a glance

TL;DR · Senior Data Scientist, Clinical Informatics (Analytics Enablement)

Senior Data Scientist - Clinical Informatics (Analytics Enablement) joins the Analytics & Behavior Change team to bridge clinical data assets with downstream consumers like analysts and business partners. This role focuses on activating clinical data repositories, ensuring information is accessible, well-documented, and compliant with regulatory standards. Key responsibilities include designing clinical data models, building feature stores, creating data dictionaries, and developing reusable data assets such as tables and views. The candidate will manage data quality frameworks, translate complex clinical concepts into analytical frameworks, and provide training to internal stakeholders. Required skills include expertise in SQL and Python, experience with large-scale healthcare datasets on Google Cloud Platform using BigQuery, and deep knowledge of standards like HL7, FHIR, ICD-10, SNOMED-CT, LOINC, CPT, NDC, and RxNorm. The role solves the challenge of transforming raw clinical data into actionable insights for improved health outcomes.

What does a Data Scientist earn in New York?

Median $173200 from 38 postings across 17 companies.

See salary data

What you'll do

  • Act as a subject matter expert on clinical data types including CCD, claims, pharmacy, and lab results.
  • Design and maintain clinical data models, taxonomies, and classification frameworks for consistent organizational use.
  • Build and manage a clinical data feature store to establish standards for downstream AI/ML and analytics.
  • Develop validated, reusable data assets such as tables and views to empower independent analysis by others.
  • Create comprehensive documentation including data dictionaries, lineage, business logic, and usage guidelines.
  • Build dashboards and visualizations to communicate data quality metrics and clinical insights to various stakeholders.
  • Partner with business units to translate complex requirements into technical data solutions.
  • Maintain data quality frameworks involving validation rules, anomaly detection, and monitoring processes.

What we're looking for

  • Bachelor's degree in health informatics, public health, nursing, computer science, statistics, or a related quantitative/clinical field.
  • Master's degree or higher in health informatics, biomedical informatics, clinical informatics, public health, or epidemiology is strongly preferred.
  • 4+ years of relevant experience in clinical informatics, healthcare analytics, or clinical data management.
  • Expertise in clinical data types including CCD, lab results, medical claims, pharmacy data, and administrative healthcare data.
  • Proficiency with coding systems such as ICD-10, CPT, SNOMED-CT, LOINC, NDC, and RxNorm.
  • Expert level SQL skills and proficiency with Python for working with large-scale healthcare datasets.
  • Experience using cloud-based platforms, preferably Google Cloud Platform (GCP) tools like BigQuery.
  • Proven ability to design data models, create documentation, and provide training/consultation to support downstream data consumers.

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