Monogram needs to develop and deploy machine learning models to support operational and clinical use cases, aiming to improve patient outcomes and quality of life while reducing medical costs.
Requirements
- 3+ years of experience performing quantitative analyses, preferably within the healthcare claims domain.
- 2+ years of experience using Python for machine learning model development and deployment.
- 2+ years of experience using SQL, Databricks & PySpark to extract and manipulate data for data engineering tasks.
- Experience with MLOps tools and practices (e.g., MLflow, GitHub Actions, Docker, model registries, Azure ML).
- Proficient in developing code and analyses following good software development practices.
- Proficiency in packaging and deploying models in production environments, ideally using Azure cloud services.
- Strong understanding of model monitoring, data drift detection, and model retraining strategies.
Responsibilities
- Own and implement end-to-end ML workflows, including model versioning, testing, containerization, automated deployment pipelines (CI/CD), and post-deployment monitoring for performance and data drift.
- Independently develop and deploy machine learning models to support Monogram’s operational and clinical objectives.
- Conduct data analyses related to model outputs or explore alternative use cases for existing models to enhance reporting and decision-making processes.
- Adhere to and promote best practices in software development, data engineering, and machine learning to ensure high-quality and maintainable code.
- Stay updated with the latest advancements in machine learning and data science, applying new techniques and methodologies to improve model performance and reliability.
- Maintain and update deployed models, ensuring their accuracy and efficiency over time, and troubleshoot any issues that arise during deployment.
- Develop machine learning models using open-source tools and libraries and may be operationalized as batch or real-time model inference endpoints.
Other
- Minimal supervision
- Collaboration with Program Owners: Engage with program owners to understand program goals, key performance indicators, and operational details to ensure that machine learning models are effectively aligned with program intentions.
- Solution Proposals: Create and present machine learning solution proposals to program owners, aiming to secure buy-in and facilitate the implementation of data-driven solutions.
- 2+ years of experience presenting technical concepts and models to business and executive stakeholders effectively.
- Strong problem-solving abilities and a proactive approach to identifying and addressing business challenges through data-driven solutions.
