AI/ML Scientist – Healthcare
Description:
- Translate business and clinical requirements into machine learning use cases focused on automation, decision support, and risk prediction in the utilization management domain
- Adapt and optimize existing machine learning techniques—including classification, NLP, and time series modeling—to address specific operational workflows and data structures
- Collaborate with developers to rapidly prototype and iterate on ML models with a focus on production-readiness, scalability, and integration into customer-facing products
- Contribute to the design of intelligent services (e.g., automated prior authorization, clinical rule learning, denial prediction) that directly impact product capabilities
- Collaborate with data engineers to acquire, preprocess, and structure healthcare data from diverse sources (claims, EHR, clinical notes)
- Perform data wrangling and feature engineering to enable robust modeling pipelines
- Evaluate and tune model performance using business-relevant metrics (e.g., precision, recall, F1, ROI), ensuring alignment with product goals and customer needs
- Partner with product managers, designers, and software engineers to embed ML capabilities into digital products and decision support tools
- Develop documentation, model APIs, and integration specifications to support seamless model deployment in production systems
- Provide insights and recommendations to support product roadmap decisions and feature prioritization
- Ensure ML solutions are reliable, maintainable, and explainable, implementing monitoring and retraining strategies to maintain performance and adapt to data drift
- Align development with healthcare compliance requirements (HIPAA, HITRUST, SOC 2) and promote ethical use of AI
- Stay up to date with emerging research in ML and health AI and conduct competitive analysis of commercial and open-source AI/ML tools
- Contribute to internal knowledge sharing and build a culture of applied innovation and product-driven development
Requirements:
- At least 3 years of experience in applied Machine Learning (ML) or data science
- 1 year of experience integrating ML into software products
- Experience working with real-world healthcare data, claims, Electronic Health Record (EHR), and clinical text
- Experience applying ML to structured and unstructured data, particularly in classification, NLP, or time series forecasting
- Strong Python programming skills
- Knowledge of ML libraries: scikit-learn, TensorFlow, PyTorch, Hugging Face, or XGBoost
- Knowledge of model evaluation, validation, and operational considerations (e.g., scalability, explainability, monitoring)
- Master’s degree in Computer Science, or a related field
- PhD in Computer Science, or a related field (listed)
- Ability to sit at a desk and utilize a computer, telephone, and other basic office equipment
- Must pass Background Screen and Drug Screen prior to employment
- Employees required to adhere to HIPAA regulations and company policies regarding confidentiality, privacy, and security of sensitive health information
- Preferred: Experience with MLOps tools and practices (e.g., MLflow, SageMaker, Airflow, Docker)
- Preferred: Familiarity with clinical coding systems (ICD, CPT, SNOMED) and interoperability standards (FHIR, HL7)
- Preferred: Background in building AI features in healthcare SaaS or digital health products
- Preferred: Awareness of AI regulatory and ethical guidelines in healthcare (e.g., model interpretability requirements)
Benefits:
- Remote - Work from home (Mountain)
- Diversity & equal employment opportunity (All qualified applicants will receive consideration)
- Drug-free workplace
- Background screen required prior to employment
- Drug screen required for newly hired employees
- Adherence to HIPAA regulations and company privacy/security policies
- California applicants have CCPA data access and correction rights (contact [email protected])
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