MRIoA is looking for an experienced and pragmatic AI/ML Scientist to drive the design and productization of machine learning solutions tailored to healthcare utilization management. This role is focused on translating proven ML research and existing algorithms into practical, scalable tools that improve operational efficiency, automate decisions, and enhance the internal and external customer experience. Working at the intersection of data science, healthcare operations, and product development, the ideal candidate excels at adapting state-of-the-art models to solve targeted, high-impact business problems.

Major Responsibilities or Assigned Duties:

Applied ML & Product Integration

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 productionreadiness, 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.

Data & Model Engineering

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.

Cross-functional Product Development

Partner closely 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.

Operationalization & Lifecycle Management

Ensure ML solutions are reliable, maintainable, and explainable, supporting long-term operation in healthcare environments.
Implement 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.

Continuous Improvement & Innovation

Stay up to date with emerging research in ML and health AI, identifying opportunities to apply new techniques pragmatically.
Conduct competitive analysis of commercial and open-source AI/ML tools, identifying components to reuse or adapt.
Contribute to internal knowledge sharing, helping build a culture of applied innovation and product-driven development.

Requirements:

Skills and Experience:

3+ years of experience in applied ML or data science, with at least 1–2 years focused on integrating ML into software products.
Strong Python programming skills and experience with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Hugging Face, XGBoost).
Proven experience working with real-world healthcare data (e.g., claims, EHR, clinical text) and understanding of common data challenges.
Experience applying ML to structured and unstructured data, particularly in classification, NLP, or time series forecasting.
Solid understanding of model evaluation, validation, and operational considerations (e.g., scalability, explainability, monitoring).
Excellent communication and collaboration skills, with the ability to work effectively in agile product development teams.

Preferred Qualifications

Experience with MLOps tools and practices (e.g., MLflow, SageMaker, Airflow, Docker).
Familiarity with clinical coding systems (ICD, CPT, SNOMED) and interoperability standards (FHIR, HL7).
Background in building AI features in healthcare SaaS or digital health products.
Awareness of AI regulatory and ethical guidelines in healthcare (e.g., model interpretability requirements).
Experience with NLP in healthcare, such as entity recognition, document classification, or summarization.

Education:

Master’s or PhD in Computer Science, AI/ML, Data Science, Applied Mathematics, or a related field.

Work Environment:

Ability to sit at a desk, utilize a computer, telephone, and other basic office equipment is required. This role is designed to be a remote position (work-from-home).

Diversity creates a healthier atmosphere: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national origin, protected veteran status, disability status, sexual orientation, gender identity or expression, marital status, genetic information, or any other characteristic protected by law.

This company is a drug-free workplace. All candidates are required to pass a Background Screen before beginning employment. All newly hired employees will take a Drug Screen, as well as agreeing to all necessary Compliance Regulations on their first day of employment.

California Consumer Privacy Act (CCPA) Information:

Sensitive Personal Info: MRIoA may collect sensitive personal info such as real name, nickname or alias, postal address, telephone number, email address, Social Security number, signature, online identifier, Internet Protocol address, driver’s license number, or state identification card number, and passport number.

Data Access and Correction: Applicants can access their data and request corrections. For questions and/or requests to edit, delete, or correct data, please email the Medical Review Institute at HR@mrioa.com.

Medical Review Institute of America

Latest Jobs

AI/ML Scientist (Remote)