Healthcare AI Data Scientist

Healthcare AI Data Scientist

Position Overview

We’re seeking a Healthcare AI Data Scientist to transform complex healthcare data into actionable insights that improve patient outcomes. In this role, you’ll analyze massive datasets from electronic health records, claims systems, and medical devices to uncover patterns, build predictive models, and inform strategic decisions. You’ll 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 data
• Conduct exploratory data analysis to identify trends, anomalies, and opportunities for AI-driven interventions
• Build dashboards and visualizations that communicate complex findings to non-technical stakeholders
• Perform 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 response
• Build risk stratification models to identify high-risk patient populations for preventive interventions
• Create propensity score models for causal inference in observational healthcare data
• Implement recommendation systems for treatment pathways and care coordination

Research & Experimentation

• Design and execute A/B tests to measure the effectiveness of AI-driven clinical interventions
• Conduct retrospective studies using real-world evidence (RWE) to answer clinical research questions
• Publish findings in peer-reviewed journals and present at healthcare data science conferences
• Stay current with healthcare AI research and translate academic findings into practical applications

Collaboration & Communication

• Partner with clinicians to frame business problems as data science questions
• Work with ML engineers to productionize research models into scalable systems
• Present insights to hospital executives, translating technical findings into strategic recommendations
• Mentor 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 data
• Implement data governance practices that ensure patient privacy and regulatory compliance
• Document data lineage, model assumptions, and analytical methodologies
• Conduct bias audits to ensure equitable AI outcomes across patient demographics

Required Qualifications

Education

• Master’s degree in Data Science, Biostatistics, Epidemiology, Health Informatics, or related quantitative field
• PhD preferred for research-focused roles
• Bachelor’s degree with 5+ years healthcare analytics experience considered

Experience

• 3+ years of experience as a data scientist, preferably in healthcare or life sciences
• Proven experience analyzing healthcare data (EHRs, claims, clinical trials, population health)
• Track record of delivering data science projects from ambiguous requirements to actionable insights
• Experience 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 databases
• Experience with statistical analysis: hypothesis testing, regression modeling, survival analysis
• Proficiency with ML libraries: scikit-learn, XGBoost, LightGBM

Visualization & Communication

• Expert-level data visualization skills using Tableau, Power BI, or matplotlib/ggplot2
• Ability to create executive dashboards that tell compelling data stories
• Experience 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, LOINC
• Familiarity with healthcare quality metrics: HEDIS, CMS Star Ratings, readmission rates
• Experience with healthcare-specific statistical methods: risk adjustment, case mix index

Cloud & Big Data (Preferred)

• Experience with cloud data warehouses: Snowflake, Redshift, BigQuery
• Knowledge of distributed computing: Spark, Dask for large-scale data processing
• Familiarity 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 forecasting
• Published research in healthcare data science (NEJM Evidence, JAMIA, JMIR)
• Knowledge of causal inference methods: propensity scores, instrumental variables, difference-in-differences
• Experience with natural language processing on clinical text
• Certifications: Certified Health Data Analyst (CHDA), SAS Certified Data Scientist

Core Competencies

• Analytical Thinking: Structured approach to breaking down ambiguous problems
• Statistical Rigor: Deep understanding of when and how to apply statistical methods
• Storytelling: Transform numbers into narratives that inspire action
• Healthcare Passion: Genuine interest in improving patient care through data
• Collaboration: Bridge technical and clinical worlds effectively
• Ethical Awareness: Commitment to responsible, equitable AI in healthcare