• Job Description

  Req#: SRDAT004845

  Position: Machine Learning Engineer

  The Machine Learning Engineer will be responsible for owning the development and deployment of machine learning models to support operational and clinical use cases at Monogram. This work will be carried out with minimal supervision, contributing to the advancement of Monogram’s data science initiatives. These models will be developed using open-source tools and libraries and may be operationalized as batch or real-time model inference endpoints. The models will utilize a variety of data sources, including healthcare claims, operational data from care management platforms, and EHRs. This position will report to the VP, Data Science with future direct reporting to the Director, Data Science.

  Roles and Responsibilities

  • MLOps / CI/CD for Models: 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.
  • Model Development and Deployment: Independently develop and deploy machine learning models to support Monogram’s operational and clinical objectives.
  • Data Analysis: Conduct data analyses related to model outputs or explore alternative use cases for existing models to enhance reporting and decision-making processes.
  • 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.
  • Technical Best Practices: Adhere to and promote best practices in software development, data engineering, and machine learning to ensure high-quality and maintainable code.
  • Continuous Improvement: Stay updated with the latest advancements in machine learning and data science, applying new techniques and methodologies to improve model performance and reliability.
  • Support and Maintenance: Maintain and update deployed models, ensuring their accuracy and efficiency over time, and troubleshoot any issues that arise during deployment.

  Position Requirements

  Experience:

  • 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).

  Technical Skills:

  • 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.
  • Experience with version control systems (GIT), CI/CD pipelines, and test-driven development.
  • Familiarity with cloud computing platforms, preferably Azure, for deploying and managing data science solutions.

  Communication and Presentation:

  • 2+ years of experience presenting technical concepts and models to business and executive stakeholders effectively.

  Educational Background:

  • Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field. A Master’s degree is a plus.

  Additional Skills:

  • Strong problem-solving abilities and a proactive approach to identifying and addressing business challenges through data-driven solutions.
  • Excellent teamwork and collaboration skills, with the ability to work effectively in cross-functional teams.

  Benefits

  • Opportunity to work in a dynamic, fast-paced, and innovative value-based provider organization that is transforming the delivery of kidney care
  • Competitive salary
  • Comprehensive medical, dental, vision and life insurance
  • Flexible paid leave and vacation policy
  • 401(k) plan with matching contributions

  About Monogram Health

  Monogram Health is a leading multispecialty provider of in-home, evidence-based care for the most complex of patients who have multiple chronic conditions. Monogram health takes a comprehensive and personalized approach to a person’s health, treating not only a disease, but all of the chronic conditions that are present - such as diabetes, hypertension, chronic kidney disease, heart failure, depression, COPD, and other metabolic disorders.

  Monogram Health employs a robust clinical team, leveraging specialists across multiple disciplines including nephrology, cardiology, endocrinology, pulmonology, behavioral health, and palliative care to diagnose and treat health issues; review and prescribe medication; provide guidance, education, and counselling on a patient’s healthcare options; as well as assist with daily needs such as access to food, eating healthy, transportation, financial assistance, and more. Monogram Health is available 24 hours a day, 7 days a week, and on holidays, to support and treat patients in their home.

  Monogram Health’s personalized and innovative treatment model is proven to dramatically improve patient outcomes and quality of life while reducing medical costs across the health care continuum. Monogram Health is based in Nashville, Tennessee, operates throughout 37 states, and is privately held by Frist Cressey Ventures, Norwest Venture Partners, TPG Capital, as well as other leading strategic and financial investors. To learn more about Monogram Health, ranked by Inc. Magazine as 2024’s No. 3 fastest growing private company in the United States, please visit here.

  Equal Opportunity Employer
  This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

• About the company

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