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Tier-1 brand, metro location, mid-level/generalist ML role with broad required skills increases competition.
Requires healthcare data, regulatory (HIPAA/FDA) knowledge and risk-modeling expertise, limiting cross-industry portability.
Mandatory 5+ years, specific ML frameworks, MLOps, and healthcare compliance create strict shortlisting filters.
Architect and develop advanced AI/ML solutions for healthcare and life sciences applications, focusing on predictive models for patient and donor risk assessment.
Design, deploy, and maintain AI models integrating them into production systems using APIs or microservices, following MLOps best practices.
Collaborate with data scientists, clinicians, and business stakeholders to optimize model performance and ensure compliance with healthcare regulations.
Bachelor’s or Master’s degree in computer science, AI, Data Science, or related field.
5+ years of experience in AI/ML development, including risk model development for classification, regression, or survival analysis.
Strong programming skills in Python (preferred), C#.Net, Java, or C++ plus experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Experience working with healthcare or life sciences data (e.g., EHR, clinical, donor datasets) and familiarity with healthcare compliance standards (HIPAA, FDA, GDPR).
Experienced AI developer with deep expertise in healthcare data and predictive risk modeling, capable of working with structured and unstructured datasets.
Skilled in full lifecycle AI development including cloud AI/ML platform usage (AWS, Azure, Google Cloud) and MLOps for model deployment and maintenance.
Capable of collaborating across interdisciplinary teams (data scientists, clinicians, business) and applying ethical AI principles including bias detection and transparency.