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Medical Review Institute of America

Medical Review Institute of America

via Indeed

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Remote AI/ML Scientist (Healthcare)

Anywhere
full-time
Posted 9/10/2025
Verified Source
Key Skills:
Machine Learning
Python programming
scikit-learn
TensorFlow
PyTorch
Hugging Face
XGBoost
ML model evaluation and validation
Healthcare data (claims, EHR, clinical text)
NLP
Time series forecasting

Compensation

Salary Range

$120K - 160K a year

Responsibilities

Design, develop, and operationalize machine learning models to improve healthcare utilization management products, collaborating cross-functionally to integrate ML into scalable software solutions.

Requirements

3+ years applied ML experience, 1+ year ML product integration, strong Python and ML libraries knowledge, healthcare data experience, and a Master’s or PhD in Computer Science or related field.

Full Description

MRIoA is seeking 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. 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. Employees are required to adhere to all applicable HIPAA regulations and company policies and procedures regarding the confidentiality, privacy, and security of sensitive health information. California Consumer Privacy Act (CCPA) Information (California Residents Only): • 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. Requirements: Skills and Experience: • 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. Hard Skills • 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). Education • Master’s degree in Computer Science, or a related field. • PhD in Computer Science, or a related field. 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).

This job posting was last updated on 9/11/2025

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