Data Scientist – Healthcare Analytics

Location: Specify Location or Remote

Employment Type: Contract

About the Role: We are seeking a highly skilled Data Scientist with deep expertise in healthcare analytics to join our team. The ideal candidate will have a strong background in machine learning, statistical modeling, and big data processing, with a focus on healthcare datasets such as EHR, claims data, clinical trial data, and population health analytics. This role requires working closely with healthcare professionals, data engineers, and product teams to drive data-driven decision-making and optimize patient outcomes.

Key Responsibilities

• Develop and deploy machine learning models to analyze large-scale healthcare datasets, including electronic health records (EHR), claims data, genomics, and real-world evidence (RWE).
• Design predictive models for disease progression, patient readmission risk, treatment effectiveness, and personalized medicine.
• Perform statistical analysis, hypothesis testing, and A/B testing on healthcare interventions.
• Work with data engineers to preprocess, clean, and structure unstructured healthcare data for analysis.
• Implement NLP techniques for analyzing clinical notes, medical records, and physician documentation.
• Optimize and improve existing algorithms for clinical decision support systems (CDSS) and healthcare operations.
• Collaborate with physicians, researchers, and regulatory teams to ensure data-driven insights comply with HIPAA, GDPR, and other healthcare regulations.
• Use data visualization techniques to communicate insights to stakeholders, including C-suite executives and healthcare providers.
• Stay updated with advancements in healthcare AI, precision medicine, and health informatics.

Required Qualifications:

• Master’s or Ph.D. in Computer Science, Data Science, Bioinformatics, Statistics, or a related field.
• 5+ years of experience in healthcare data science, with a strong understanding of healthcare terminologies and workflows.
• Expertise in Python, R, SQL, Spark, and deep learning frameworks like TensorFlow or PyTorch.
• Experience working with EHR (Epic, Cerner), claims databases, HL7, FHIR, OMOP, or other healthcare data standards.
• Strong understanding of biostatistics, epidemiology, and healthcare economics.
• Familiarity with regulatory and compliance frameworks (HIPAA, GDPR, FDA guidelines for AI/ML in healthcare).
• Proficiency in cloud platforms (AWS, Azure, GCP) for handling large-scale healthcare datasets.
• Experience with NLP for medical text processing is a plus.
• Ability to work in a cross-functional team and communicate findings to both technical and non-technical stakeholders.

Preferred Qualifications

• Prior experience in pharmaceutical, biotech, or health-tech startups.
• Knowledge of clinical trials, real-world evidence (RWE), and drug discovery processes.
• Experience with predictive modeling for patient outcomes and risk stratification.
• Publications or contributions in healthcare AI or bioinformatics research.