Applied AI Data Scientist

Applied AI Data Scientist at Flatiron Health

Flatiron Health is dedicated to improving and extending lives by learning from the experience of every person with cancer. We are seeking an Applied AI Data Scientist to join our mission and become a changemaker in cancer care.

As a healthtech company, Flatiron Health leverages data to power smarter care for individuals with cancer globally. We collaborate with cancer centers across the US, Europe, and Asia, transforming real-life patient experiences into real-world evidence. Our multidisciplinary teams, including oncologists, data scientists, software engineers, and epidemiologists, contribute to a modern, connected oncology ecosystem. Flatiron Health operates as an independent affiliate of the Roche Group.

What You'll Do

At Flatiron, we are advancing the use of machine learning and generative AI to extract crucial clinical information from unstructured medical notes, enabling cutting-edge oncology research. The Data Curation team is instrumental in building these next-generation research data products, employing ML and LLMs to capture a comprehensive picture of the patient journey.

In this role, you will apply existing internal and external AI systems, validating AI-generated datasets used by clinicians and researchers. These datasets are vital for evolving cancer research, generating clinical insights, and learning from the experiences of thousands of people living with cancer. You will engage with a cross-functional group of stakeholders across our global teams (Europe, Japan, and the US), contributing to the development of ML-derived datasets from initial scoping through validation, productionization, and delivery.

Additionally, you will:

• Work with clinical stakeholders to apply existing AI systems, converting raw clinical data into high-quality research data.
• Become a subject matter expert on our data and its capabilities, collaborating closely to understand data needs and provide analytical support for model development and deployment.
• Partner with research scientists and oncologists to validate that our team’s models produce sound scientific insights, including comprehensive dataset performance analyses.
• Collaborate with subject matter experts and ML researchers to define requirements for training and evaluation datasets, and maintain software pipelines for their generation.
• Provide analytical support and create custom data outputs for cross-functional teams, including our clinical experts.
• Interface with internal scientific and clinical stakeholders to ascertain their data requirements for conducting high-quality research.
• Work cross-functionally with software engineers to productionize, scale, and monitor our team’s models.

Who You Are

You are a product-focused Applied AI Data Scientist with creative analytical problem-solving skills, eager to tackle challenges in measuring the performance of complex datasets and the systems that build them. You are enthusiastic about learning oncology from our clinical stakeholders and applying AI to extract nuanced clinical concepts from medical records. You will validate the fitness-for-use of this data for oncology research. You are a kind, passionate, and collaborative problem-solver who values candid feedback and seeks to make a significant impact.

Your qualifications include:

• 3+ years of relevant working experience as an applied data scientist or in a similar technical data-oriented role, including relevant applied work in an academic setting.
• Some experience working with ML or LLMs.
• An understanding of how machine learning and AI systems are measured; you can analyze existing systems to assess output quality, identify areas for improvement, and communicate their impact to stakeholders.
• A clear and confident communicator, capable of breaking down complex data analyses into compelling narratives.
• Excitement to work in a startup environment, demonstrating creativity and resourcefulness to achieve goals, with a strong sense of value and empathy for customers.
• Experience collaborating with technical team members in a production development environment using formal version control, Python (including data manipulation in pandas, polars, or similar frameworks), and SQL.
• Proficiency in both English and German.

Extra Credit (Optional)

• Experience working with data in a healthcare setting.
• Experience with the risks of bias in machine learning, health equity research/analysis, or working with underrepresented groups in a clinical research setting.
• Experience working in dbt or other ETL frameworks.
• Experience with deep learning and traditional NLP methods.

Key skills/competency

• Machine Learning
• Generative AI
• Large Language Models (LLMs)
• Data Validation
• Oncology Research
• Clinical Data Extraction
• Python Programming
• SQL
• Data Analysis
• Stakeholder Collaboration