Flatiron Health’s mission is to serve cancer patients and our customers by dramatically improving treatment and accelerating research. Our team is building a disruptive, oncology-specific software platform that connects cancer centers across the world on a common technology infrastructure to address key healthcare challenges.
Our engineering team
The Flatiron Health engineering team builds and runs data processing pipelines, algorithmic and human-operated data curation tools, and customer-facing data analytics and visualization tools. We build systems that clean, structure and understand clinical-level patient data as we build the largest, most comprehensive set of oncology data intelligence. We scale pipelines to handle the world's oncology data with creative engineering solutions to open-ended oncology data problems. Read about our engineering culture!
Our data pipeline takes in full clinical patient records and produces normalized, high-fidelity, queryable data that is ready to be mined for medical and operational insights. We’ve built a unified data set that is unparalleled in its depth and accuracy, and gives our partners the capability to ask questions about data that weren't answerable before now.
We work in a fast-paced, high-information-volume environment with complex domain challenges, which means context is key and there's always more to learn and soak up. We want to know oncology data cold — better than anyone else in the industry — and we believe doing that requires building a culture where we all like coming to work each day. In our culture, decisions are transparent and data-driven, and people are empowered to make waves.
Are you interested in changing the way the oncology world thinks about data?
As a Flatiron Software Engineering Research Intern, you will:
- Explore algorithmic and statistical techniques using our data to improve products and to scale more quickly
- Run experiments and implement prototypes that will inform key product development decisions
- Work cross-functionally to incorporate ideas and expertise from our engineering, statistics, and clinical teams
- You are in a computer science, medical informatics, statistics, or related degree program
- You have advanced coursework, research, or industry experience in machine learning, natural language processing, or medical informatics
- You understand experimental design and can build for collection, measurement and interpretation of results
- You value impact, are results-oriented, and care about the details
- You are comfortable building and working with data pipelines in languages such as Python, R, Java, C/C++, or Scala
- You are enthusiastic about working on a multi-disciplinary team
- You are passionate about our mission to improve healthcare through data and software
- You are in a Ph.D. program focusing on machine learning, natural language processing, or medical informatics
- You have experience working with clinical data
- You have experience building production machine learning systems
- You have experience with Python, numpy, scikit-learn, and R