Healthcare AI Data Scientist
Location: Phoenix, Arizona, US
Recruiter: HealthTECH Resources
Date posted: Monday, November 24, 2025
Job Description:
Healthcare AI Data Scientist
Position Overview
Were seeking a Healthcare AI Data Scientist to transform complex healthcare data into actionable insights that improve patient outcomes. In this role, youll analyze massive datasets from electronic health records, claims systems, and medical devices to uncover patterns, build predictive models, and inform strategic decisions. Youll collaborate with clinical teams, ML engineers, and hospital executives to translate data into stories that drive healthcare transformation.
Location:Remote (U.S. based) with quarterly on-site meetings
Salary Range:$110,000 $150,000 + Performance Bonus
Employment Type:Full-Time
Key Responsibilities
Data Analysis & Insights
Analyze complex healthcare datasets including EHRs (Epic, Cerner), claims (CMS, commercial payers), and patient-generated dataConduct exploratory data analysis to identify trends, anomalies, and opportunities for AI-driven interventionsBuild dashboards and visualizations that communicate complex findings to non-technical stakeholdersPerform statistical analysis to validate hypotheses and measure the impact of healthcare interventions Predictive Modeling & ML
Develop predictive models for clinical outcomes: readmission risk, disease progression, treatment responseBuild risk stratification models to identify high-risk patient populations for preventive interventionsCreate propensity score models for causal inference in observational healthcare dataImplement recommendation systems for treatment pathways and care coordination Research & Experimentation
Design and execute A/B tests to measure the effectiveness of AI-driven clinical interventionsConduct retrospective studies using real-world evidence (RWE) to answer clinical research questionsPublish findings in peer-reviewed journals and present at healthcare data science conferencesStay current with healthcare AI research and translate academic findings into practical applications Collaboration & Communication
Partner with clinicians to frame business problems as data science questionsWork with ML engineers to productionize research models into scalable systemsPresent insights to hospital executives, translating technical findings into strategic recommendationsMentor junior data analysts and contribute to team knowledge sharing Data Quality & Governance
Assess data quality issues and develop strategies for cleaning, imputing, and validating healthcare dataImplement data governance practices that ensure patient privacy and regulatory complianceDocument data lineage, model assumptions, and analytical methodologiesConduct bias audits to ensure equitable AI outcomes across patient demographics Required Qualifications
Education
Masters degree in Data Science, Biostatistics, Epidemiology, Health Informatics, or related quantitative fieldPhD preferred for research-focused rolesBachelors degree with 5+ years healthcare analytics experience considered Experience
3+ years of experience as a data scientist, preferably in healthcare or life sciencesProven experience analyzing healthcare data (EHRs, claims, clinical trials, population health)Track record of delivering data science projects from ambiguous requirements to actionable insightsExperience presenting analytical findings to executive leadership and clinical stakeholders Technical Skills
Programming & Analysis
Expert proficiency in Python (pandas, NumPy, scikit-learn) or R (tidyverse, caret)Advanced SQL skills for complex queries across relational databasesExperience with statistical analysis: hypothesis testing, regression modeling, survival analysisProficiency with ML libraries: scikit-learn, XGBoost, LightGBM Visualization & Communication
Expert-level data visualization skills using Tableau, Power BI, or matplotlib/ggplot2Ability to create executive dashboards that tell compelling data storiesExperience with tools like Jupyter notebooks, R Markdown for reproducible research Healthcare Analytics
Understanding of healthcare data structures: EHR schemas, claims formats (837, FHIR)Knowledge of medical coding systems: ICD-10, CPT, SNOMED, LOINCFamiliarity with healthcare quality metrics: HEDIS, CMS Star Ratings, readmission ratesExperience with healthcare-specific statistical methods: risk adjustment, case mix index Cloud & Big Data (Preferred)
Experience with cloud data warehouses: Snowflake, Redshift, BigQueryKnowledge of distributed computing: Spark, Dask for large-scale data processingFamiliarity with data orchestration tools: Airflow, dbt Preferred Qualifications
Clinical background (RN, MD, PharmD) or public health degree (MPH, DrPH)Experience with longitudinal data analysis and time-series forecastingPublished research in healthcare data science (NEJM Evidence, JAMIA, JMIR)Knowledge of causal inference methods: propensity scores, instrumental variables, difference-in-differencesExperience with natural language processing on clinical textCertifications: Certified Health Data Analyst (CHDA), SAS Certified Data Scientist Core Competencies
Analytical Thinking:Structured approach to breaking down ambiguous problemsStatistical Rigor:Deep understanding of when and how to apply statistical methodsStorytelling:Transform numbers into narratives that inspire actionHealthcare Passion:Genuine interest in improving patient care through dataCollaboration:Bridge technical and clinical worlds effectivelyEthical Awareness:Commitment to responsible, equitable AI in healthcare
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