San Mateo, CA
At Roam, our mission is to improve global health by bringing comprehensive knowledge to patients, providers, professionals, and life sciences companies.
The Roam platform is powered by machine learning and a proprietary data asset we call the Roam Health Knowledge Graph. The Roam Health Knowledge Graph is continuously enriched through self-learning algorithms that map connections, relationships and causal pathways across trillions of disparate structured and unstructured data points. The result is an unprecedented, comprehensive view of the healthcare industry that allows pharmaceutical companies to follow information instead of instincts when seeking to improve patient outcomes.
We are looking for a machine learning engineer to join our growing analytics team. At Roam, analytics and machine learning are the lifeblood of our company. With deep ties to academia, the team is highly collaborative and places a strong emphasis on pragmatic research. Roam doesn’t simply use machine learning in various parts of our product; machine learning is the bedrock of everything we do. The work is diverse, and at Roam you’ll be presented with tasks that require knowledge of featurization, classification, entity resolution, and bespoke predictive modeling. You’ll have at your disposal the largest, highest-quality graph of healthcare data ever developed. And finally, you’ll play a key role in developing tools and abstractions that our other developers will build on.
- Develop and extend a knowledge graph building pipeline.
- Develop predictive models (supervisory and deep learning) that elucidate and clarify critical business problems in the healthcare industry
- Aid in the development, expansion, and maintenance of the Health Knowledge Graph
- Deep understanding of the mathematical foundations of Machine Learning algorithms
- Previous experience or side projects building end to end Machine Learning systems
- Experience with Python, Jupyter, and Elasticsearch
- Experience applying statistical algorithms to real world data
- Passion for healthcare and this high impact problem
- MS or PhD in Computer Science, Engineering, Statistics or a related field