Machine Learning Researcher
About The Position
At Komodo Health, our mission is to reduce the global burden of disease. And we believe that smarter use of data is essential to this mission. That’s why we built the Healthcare Map — the industry’s largest, most complete, precise view of the U.S. healthcare system — by combining de-identified, real-world patient data with innovative algorithms and decades of clinical experience. The Healthcare Map serves as our foundation for a powerful suite of software applications, helping us answer healthcare’s most complex questions for our partners. Across the healthcare ecosystem, we’re helping our clients unlock critical insights to track detailed patient behaviors and treatment patterns, identify gaps in care, address unmet patient needs, and reduce the global burden of disease. As we pursue these goals, it remains essential to us that we stay grounded in our values: be awesome, seek growth, deliver “wow,” and enjoy the ride. At Komodo, you will be joining a team of ambitious, supportive Dragons with diverse backgrounds but a shared passion to deliver on our mission to reduce the burden of disease — and enjoy the journey along the way. The Opportunity at Komodo Health: As an ML Researcher, you will be at the core of developing the proprietary models that power our Healthcare Map and the Marmot generative AI platform. You will bridge the gap between theoretical machine learning and practical, high-scale application, conducting original research to improve our ability to link, de-duplicate, and normalize complex longitudinal patient data. This is not just an academic role; we are looking for a researcher with a "Platform Builder" mindset who is eager to move beyond experimental code to create durable, versioned models that enhance our data infrastructure and AI capabilities.
Requirements
- Advanced Research Background: Deep expertise in Machine Learning, Statistics, or a related quantitative field with a strong track record of "solution-oriented" research.
- Python Mastery: Expert-level proficiency in Python and the broader ML stack for custom API connector development and data reconciliation.
- Proficiency in Quantitative Reasoning: An ability to understand complex data nuances and use that knowledge to scope out technical solutions for platform-level challenges.
- Curiosity & Initiative: A proactive drive to explore new AI tools and workflows, with a commitment to sharing AI-enhanced automations with the broader team.
- Collaborative Communicator: Ability to translate complex model limitations and research findings into actionable insights for both technical and non-technical stakeholders.
Responsibilities
- Execute Original Research: Design and test new ML architectures to solve challenges in data integration, interoperability, and predictive modeling across diverse datasets.
- Collaborate on Model Architecture: Partner closely with Product and Engineering to ensure research efforts align with revenue-critical IAM and data-orchestration goals.
- Adopt a Reflexive AI Mindset: Use AI as a natural part of your own research process to iterate faster and deliver higher-quality code and documentation.
- Ensure Technical Excellence: Maintain the highest standards of technical accuracy, ensuring that all models are robust, scalable, and built for a high-performance SaaS environment.
- Automate Data Reconciliation: Build API-driven reconciliation jobs and data normalization scripts to ensure a unified and consistent view across our data estate.
Benefits
- comprehensive health, dental, and vision insurance
- flexible time off and holidays
- 401(k) with company match
- disability insurance and life insurance
- leaves of absence in accordance with applicable state and local laws and regulations and company policy
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
