Machine Learning Engineer, Flatiron Health

• You're a product-focused data scientist, with experience in leveraging ML and NLP to solve real-world problems
• You're excited by the prospect of rolling up your sleeves to tackle meaningful problems each and every day. You’re a kind, passionate and collaborative problem-solver who seeks and gives candid feedback, and values the chance to make an important impact
• You have 3+ years of relevant working experience in a technical capacity, with a focus on ML. Prior experience with NLP and LLMs is strongly preferred
• You have a strong background in applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML
• You are excited to work in a startup environment, think creatively and be scrappy to get the job done. You have a nose for value and empathy for your customers
• You have collaborated with other technical team members in a production development environment using formal version control, Python, and SQL

Desirable

• We’re looking for a Data Scientist, Machine Learning to help us accomplish our mission to improve and extend lives by learning from the experience of every person with cancer
• At Flatiron, we’re advancing the use of machine learning, generative AI, and natural language processing to extract clinically relevant information from unstructured medical notes for use in oncology research.
• The Discovery team is helping to build these next generation research data products, developing and applying ML models to capture a complete picture of the patient journey. While most of the team are Data Scientists and ML Engineers, Discovery has team members spanning 5 different fields, from data science to product management to research oncology
• As part of our team, you will develop and validate models to solve applied clinical problems and help build towards our vision of the future of machine learning at Flatiron. Engaging with a cross-functional group of stakeholders both within Discovery and across the company, you will contribute to model development projects from scoping through to productionization and delivery
• Interface with internal scientific stakeholders and customers to understand what data they need to conduct high quality research
• Build models to turn raw clinical data into high quality research variables, drawing on your knowledge of LLMs, traditional ML, and NLP techniques to determine the right methods to use for a given problem
• Work with quantitative scientists and oncologists to validate that your models can be used to generate sound scientific insights
• Collaborate with other Machine Learning EngineersData Scientists to accelerate our ML capabilities and develop novel approaches to clinical data extraction from unstructured health records
• Work cross-functionally with software engineers to productionize, scale, and monitor your models