Summer 2025 Data Science & Machine Learning Intern
Flatiron Health, New York, NY, United States
Reimagine the infrastructure of cancer care within a technology and science community that values integrity, inspires growth, and is uniquely positioned to create a more modern, connected oncology ecosystem.
We're looking for Summer 2025 Data Science & ML Interns to help us accomplish our mission to improve lives by learning from the experience of every cancer patient. Are you ready to be the next changemaker in cancer care?
What You'll DoAs a Data Science & ML Intern, you will work with a diverse and talented team with expertise in digging into open-ended customer problems, prototyping, and rapidly iterating on data products from initial discovery to production. As part of our team, you will develop and validate machine learning 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 across the company, you will contribute to machine learning model development projects from scoping through to productionization and delivery.
The Data Insights team has worked on products to enable healthcare providers to manage cancer centers and treat patients more easily, and developed tools to help Life Sciences companies to accelerate cancer research. Some example projects we've worked on include:
- An algorithm that assesses how a provider should be billing payers for provided services to optimize for charges getting paid out
- Exploration of retrieval augmented generation as a new approach to data extraction from unstructured clinic visit notes
- Using ElasticSearch and NLP to demonstrate the utility of unstructured data for quality analytics (e.g. hospice referrals, and context surrounding death)
- Turn good ideas into prototypes, and prototypes into early stage products
- Learn how healthcare data works by building data pipelines using Python and/or SQL
- Develop knowledge of healthcare industry trends and data
- 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
- You have experience coding in a data-centric programming language such as Python, Pandas, and SQL
- You have a strong understanding of applying ML to solve real-world problems and a solid grasp of the underlying statistical fundamentals of ML
- You are a self-starter who can and independently prioritize and address problems in a highly ambiguous environment
- You are a clear and confident communicator who can break down complex data analysis to tell a compelling story
- You are passionate about our mission to improve cancer care through data and technology
- You are interested in at least one of these fields: data analytics, decision science, machine learning, operations research, data modeling, business intelligence, or data engineering
Where you'll workIn this hybrid role, you'll have a defined work location that includes work from home and 3 office days set by you and your team. For more information on our approach to hybrid work, please visit the how we work website.
Job Compensation Range
Salary Range: $100,000 - $100,000
Preferred Primary Location: NYC Headquarters
An important note on salary
The annual pay range reflected above for this position is based on the preferred primary location of the role which is listed in the job description. Salary ranges for other locations vary from the range reflected above. Base pay offered may vary depending on job-related knowledge, skills, and experience. An annual bonus and equity may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered
Flatiron Health is proud to be an Equal Employment Opportunity employer.
We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.