Data Scientist

Job Title: Data Scientist Location: Houston, TX (Hybrid/Onsite) Long Term Contract Need Recent Healthcare clients experience Job Description: • As part of our growing Data Science & AI team, we are seeking a Data Scientist who is passionate about data, innovation, and healthcare transformation. In this role, you will develop predictive models and advanced analytics solutions that directly impact patient care delivery, operational efficiency, and healthcare cost optimization. Where You Fit In: • As a Data Scientist, you will design and implement machine learning models, predictive analytics, and data-driven solutions for the client's platforms. You will work cross-functionally with clinical SMEs, engineering teams, and product stakeholders to transform raw healthcare data into actionable insights. • Your contributions will support areas such as patient risk stratification, hospital readmission prediction, disease progression forecasting, and operational demand forecasting. Key Responsibilities: • Analyze large healthcare datasets (EHR, claims, clinical, operational) to identify patterns and create datasets for predictive modeling. • Build and deploy machine learning models to forecast healthcare demand, patient risk, and clinical outcomes. • Integrate predictive analytics into downstream healthcare applications such as care management, revenue cycle optimization, and reporting. • Develop dashboards and visualizations to monitor performance, outcomes, and accuracy of predictive models. • Collaborate with product managers, clinicians, and engineering teams to ensure models address real-world healthcare needs. • Communicate technical details and insights to both technical and non-technical stakeholders. • Stay current with advancements in healthcare analytics, AI/ML techniques, and regulatory compliance (HIPAA). Qualifications: Required: • Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. • 1–3 years of experience using SQL to query large datasets in cloud-based environments. • 1–3 years of experience in Python-based ML development (scikit-learn, TensorFlow, or PyTorch). • Strong background in statistics, mathematics, and probability modeling. • Hands-on experience with data visualization (Power BI, Tableau, or similar). • Excellent communication skills to explain technical findings to business and clinical stakeholders. Preferred (Nice to Have): • Experience with healthcare datasets (EHR, claims, HL7, FHIR, etc.). • Familiarity with cloud ML platforms (AWS Sagemaker, Azure ML, Databricks). • Experience with data engineering frameworks (Airflow, dbt, Docker, Kubernetes). • Knowledge of Bayesian modeling, time-series forecasting, or probabilistic modeling.