Healthcare Data Scientist

About Med Clinic X

Med Clinic X is a healthcare technology company focused on building advanced AI-driven digital health systems for healthcare organizations across the United States.

We design and develop healthcare SaaS platforms, patient portals, AI-powered clinical systems, telemedicine solutions, automation tools, and data-driven healthcare products for clinics, hospitals, and healthcare providers.

Our mission is to transform healthcare using data, machine learning, and intelligent systems that improve patient outcomes and operational efficiency.

We are seeking a Healthcare Data Scientist to design and build advanced analytics models, machine learning systems, and AI-driven healthcare solutions.

In this role, you will work with large-scale healthcare datasets from clinical systems, EHR platforms, and SaaS applications to build predictive models and intelligent systems that support healthcare decision-making.

You will collaborate with engineers, product teams, clinical stakeholders, and data analysts to develop AI solutions that power the next generation of digital healthcare products.

• Build predictive models for healthcare outcomes and clinical insights.
• Develop machine learning algorithms using structured and unstructured healthcare data.
• Design AI systems for patient risk prediction and operational optimization.
• Train and evaluate models using real-world healthcare datasets.

• Analyze complex healthcare datasets from multiple clinical sources.
• Identify trends, patterns, and correlations in clinical and operational data.
• Develop statistical models to support healthcare decision-making.
• Perform feature engineering for healthcare AI systems.

• Support AI features for healthcare SaaS platforms and patient portals.
• Improve personalization and automation in healthcare applications.
• Analyze user behavior and system performance in digital health platforms.
• Build data-driven insights for healthcare product teams.

• Work with engineers to deploy machine learning models into production systems.
• Collaborate with product managers to define AI-driven healthcare features.
• Support integration of AI models with healthcare APIs and platforms.
• Ensure scalability and reliability of healthcare AI systems.

• Train and evaluate models for disease diagnosis, clinical risk mapping, and workflow assistant tools.

• Build models to estimate readmission risks, hospital length of stay, and operational bottlenecks.

• Support clinical decision-making by surfacing patient flags directly in doctor queues.

• Engineer features from longitudinal patient charts to map cardiac, diabetic, and respiratory risk trajectories.

• Leverage LLMs and clinical BERT to extract medical terms, intents, and symptoms from doctor notes.

• Deploy SaaS intelligence layers optimizing doctor schedules and automating intake briefs.

• Machine Learning Frameworks Required
• Python (Pandas, Num Py, Scikit)
  Required
• Statistical & Predictive Modeling Required
• Deep Learning (Tensor Flow/PyTorch)
  Highly Valued
• EHR/EMR Dataset architectures
  
  Highly Valued

• HIPAA Compliance & MLOps Preferred
• Bachelor’s or Master’s in Data Science, CS, Stats, ML, or related field.
• Strong experience in statistical modeling and predictive machine learning.
• Proficiency in Python and standard ML libraries (Pandas, Scikit-learn).
• Experience with SQL and relational/non-relational database query optimization.

• Experience in US healthcare or healthcare SaaS platforms.
• Knowledge of HIPAA regulations, anonymization, and data privacy.
• Experience working with large EMR/EHR datasets or clinical notes.
• Knowledge of HL7, FHIR, or healthcare data standards.

• Build ML systems directly used to improve real-world US clinical delivery.
• Analyze large-scale, high-complexity longitudinal patient datasets.
• Collaborate with top-tier engineers and clinical decision makers.