Healthcare AI Machine Learning

Healthcare AI Machine Learning

Fully Remote

12 Months

As a Recommendation System ML and AI Contractor at Kaiser Permanente, you will play a critical role in developing and optimizing advanced recommendation algorithms and systems. Your focus will be on creating solutions that personalize patient care, improve service delivery, and support decision-making processes through sophisticated data-driven insights.

Key Responsibilities:

• Algorithm Design and Development: Develop and implement recommendation algorithms using machine learning and AI techniques tailored to healthcare applications, including collaborative filtering, content-based filtering, and hybrid models.
• Data Analysis and Insights: Analyze healthcare data, including patient records and clinical data, to identify trends, patterns, and insights that enhance recommendation accuracy and relevance.
• Model Training and Evaluation: Train, validate, and refine recommendation models using appropriate machine learning frameworks and methodologies, ensuring alignment with healthcare standards and practices.
• System Integration: Collaborate with IT and engineering teams to integrate recommendation models into existing healthcare systems and workflows, ensuring seamless functionality and scalability.
• Performance Monitoring and Optimization: Continuously monitor the performance of recommendation systems, leveraging user feedback and performance metrics to implement improvements and maintain high-quality recommendations.
• Collaboration: Work closely with healthcare professionals, data scientists, and product managers to ensure that recommendation systems meet clinical and operational needs and align with Kaiser Permanente's strategic objectives.
• Documentation and Reporting: Create and maintain comprehensive documentation for algorithms, models, and processes, and provide regular updates and reports on system performance and development progress.

Requirements:

• Experience: Demonstrated experience in developing recommendation systems using machine learning and AI, preferably in a healthcare or related domain.
• Technical Proficiency: Strong programming skills in languages such as Python, R, or Java, and experience with machine learning frameworks like TensorFlow, PyTorch, or Scikit-Learn.
• Data Handling Expertise: Proficient in data manipulation and analysis using tools such as Pandas, NumPy, and visualization libraries like Matplotlib or Seaborn.
• Healthcare Knowledge: Familiarity with healthcare data types, privacy regulations (e.g., HIPAA), and the specific challenges associated with healthcare recommendations.
• Problem-Solving Skills: Excellent analytical skills with the ability to address complex challenges and devise innovative solutions tailored to healthcare applications.
• Communication Skills: Strong verbal and written communication abilities, with experience explaining technical concepts to both technical and non-technical stakeholders.
• Educational Background: Degree in Computer Science, Data Science, Statistics, or a related field, or equivalent professional experience.

Preferred Qualifications:

• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and deployment of machine learning models in a cloud environment.
• Knowledge of big data technologies (e.g., Hadoop, Spark) and experience with large-scale healthcare data.
• Previous experience working in a healthcare setting or with healthcare-related projects.

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