Job Title : Data Scientist
Location : Miami, Florida, United States
Job Type : Full Time
Job Summary
Our client is seeking an experienced Data Scientist to advance analytics and AI initiatives supporting pediatric healthcare, precision medicine, and operational excellence.
Key Responsibilities:
- Applies advanced analytics—including machine learning, natural language processing, and AI—to interpret structured and unstructured healthcare datasets such as clinical, genomic, and operational information.
- Creates predictive models that combine multi-omics data, biomarkers, and clinical indicators to enable personalized medicine and tailored treatment pathways.
- Designs scalable data pipelines and integrates complex datasets using graph-based technologies to reveal meaningful patterns across patient populations, treatments, and outcomes.
- Works with data engineering and IT teams to deploy models into production for real-time insights, risk assessment, and resource planning within clinical and administrative settings.
- Develops and validates predictive tools that support clinical decision-making, risk stratification, and outcome forecasting for pediatric patients.
- Ensures all work adheres to regulatory standards, institutional policies, and ethical guidelines related to healthcare data and PHI.
- Partners closely with clinicians, researchers, and operational leaders to understand needs, design analytic solutions, and communicate results effectively.
- Maintains clear, thorough documentation to support reproducibility of methods, analytical processes, and research outcomes.
- Serves as a technical resource and mentor for team members, fostering best practices in data science and healthcare analytics.
Minimum Qualifications:
- Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Biostatistics, Bioinformatics, or a related quantitative discipline.
- 3–5 years of professional experience in data science, preferably within healthcare or the life sciences.
- Hands-on experience with healthcare datasets such as EHRs, clinical databases, or ERP systems.
- Demonstrated ability to apply statistical methods and machine learning techniques to real-world healthcare or operational challenges.
Preferred Knowledge, Skills, and Abilities:
- Master’s degree in a quantitative or computational field.
- Strong programming skills in Python, R, and SQL.
- Deep understanding of statistical modeling, machine learning, and data visualization.
- Experience with large language models and foundation models for clinical text analysis.
- Familiarity with graph databases (e.g., Neo4j, Amazon Neptune) and vector databases (e.g., Pinecone).
- Exposure to precision medicine, genomic datasets, or personalized care analytics.
- Experience with distributed computing, big data ecosystems, and cloud environments (AWS, Azure, GCP).
- Understanding of healthcare systems, including EHR platforms and multi-source data integration.
- Knowledge of regulatory frameworks such as HIPAA, FDA guidelines, and clinical research compliance.
- Familiarity with clinical coding standards (ICD-10, CPT, SNOMED).
- Strong communication skills, with the ability to convey complex technical concepts to diverse audiences.
- Ability to work effectively with interdisciplinary teams involving clinicians, researchers, and technology specialists.
- Proven skill in translating organizational needs into actionable technical solutions.
- Detail-oriented with a strong commitment to data quality and accuracy.
- Capable of managing multiple priorities and meeting project deadlines.
- Self-driven and collaborative, able to work independently while contributing to team success.
