Data Science Platform Researcher

Verily is a subsidiary of Alphabet that is using a data-driven approach to change the way people manage their health and the way healthcare is delivered. Launched from Google X in 2015, our purpose is to bring the promise of precision health to everyone, every day. We are focused on generating and activating data from a variety of sources, including clinical, social, behavioral and the real world, to arrive at the best solutions for a person based on a comprehensive view of the evidence. Our unique expertise and capabilities in technology, data science and healthcare enable the entire healthcare ecosystem to drive better health outcomes.

This is a paid 12-month program for graduate students who are interested in working at the intersection of technology, data science, and healthcare. The program is designed for all students, and again this year we encourage students who have been historically underrepresented in this field to explore the program, which is a pathway towards full-time employment within Verily. This includes but is not limited to: Black/African-American, Latinx/Hispanic, Native American, students with disabilities, veterans, and non-binary people.

As a PhD Research Scholar on the Clinical AI team at Verily, you will contribute to our mission of transforming healthcare through scalable, real-world data (RWD) curation and AI-driven tools. You’ll work on key problems involving electronic health records (EHRs), clinical narratives, and foundational models to help us build high-quality longitudinal datasets and intelligent systems that power precision health at scale. This internship provides the opportunity to lead independent research, publish findings, and work collaboratively with engineering, clinical, and product teams.

Join us for a unique 6-month OR 12-month Research Scholar program starting in 2025.

• Collaborate with cross-functional teams to develop and refine machine learning models using real-world healthcare data.

• Design and prototype NLP/LLM solutions to extract insights from unstructured clinical text.

• Support development of foundational datasets through multi-source data integration and clinical concept abstraction.

• Conduct literature reviews and comparative evaluations to inform model design and healthcare applications.

• Communicate progress through internal presentations and, where applicable, contribute to academic publications.

Minimum Qualifications:

• Currently pursuing a PhD in Computer Science, Biomedical Informatics, Statistics, Data Science, or a related technical field.

• 2+ years of experience applying machine learning or NLP to clinical or real-world healthcare data.

• Strong programming skills in Python and experience with ML/NLP frameworks such as TensorFlow, PyTorch, or HuggingFace.

• Experience working with electronic health records (EHRs), clinical notes, or medical ontologies.

Preferred Qualifications:

• Familiarity with large language models (LLMs), including prompting, fine-tuning, or retrieval-augmented generation (RAG).

• Knowledge of medical terminologies (e.g., SNOMED CT, ICD-10, RxNorm) and ontological structuring.

• Experience developing production-ready ML pipelines or tools in healthcare or life sciences.

• Strong communication skills and ability to work collaboratively with technical and non-technical stakeholders.

• Interest in translating research into real-world, scalable applications.

The US hourly range for this Research Scholar position is $53–$63 + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.