Who We Are
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.
Description
As a Senior Data Scientist on our Registries and RWD (real-world data) team, you will be supporting our core mission to drive innovation in evidence generation for research and care decisions. We are building new types of longitudinal datasets that have foundations of RWD sources, such as EHRs (electronic health records) and claims data, and are augmented with prospective data collection. You will develop and deploy models that enable scalable curation of RWD. This will include multi-source integrations and reconciliations, creating derived features from the source data (e.g., abstraction of clinical concepts from unstructured data), and facilitating data quality assessments. You will work with a diverse cross-functional team to build reusable and scalable tools and to deliver products that unlock information from structured and unstructured clinical data.

Responsibilities

• Work closely with cross-functional partners to design and create longitudinal datasets integrating multiple data sources.
• Build and implement highly accurate machine learning models / AI tools using sparsely labeled healthcare datasets.
• Implement, build on and augment existing LLM/NLP tools to maximize the value of using unstructured medical data across a range of research and care applications.
• Become an expert in our data’s capabilities and limitations. Solve difficult, non-routine analysis problems, handling data challenges from a real-world setting.
• Communicate technical methods and results clearly in well structured reports and presentations to a range of technical and non-technical audiences.

Qualifications

Minimum Qualifications

• Advanced degree in a quantitative discipline (e.g., data sciences, statistics, biomedical informatics, computer science, applied mathematics, or similar), or equivalent practical experience.
• 2+ years experience applying advanced machine learning and AI techniques (supervised and unsupervised methods, LLMs, NLP) to clinical data.
• Direct experience working with and curating real-world data, such as EHR, including a deep understanding of the complexities of this structured and unstructured clinical data.
• Strong proficiency in Python.

Preferred Qualifications

• Familiarity with medical terminologies and ontologies.
• Familiarity with software engineering practices and experience developing production software.
• Experience working with clinical subject matter experts.
• Ability to work cross-functionally on teams, with a tolerance for ambiguity.
• Creative and methodical problem solving: understand needs, identify options, form hypotheses, generate robust results, make informed decisions, and learn faster through feedback.

This role is eligible for Verily-sponsored immigration support.
The US base salary range for this full-time position is $119,000 - $169,000 + bonus + equity + 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.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus or benefits

• Work closely with cross-functional partners to design and create longitudinal datasets integrating multiple data sources.
• Build and implement highly accurate machine learning models / AI tools using sparsely labeled healthcare datasets.
• Implement, build on and augment existing LLM/NLP tools to maximize the value of using unstructured medical data across a range of research and care applications.
• Become an expert in our data’s capabilities and limitations. Solve difficult, non-routine analysis problems, handling data challenges from a real-world setting.
• Communicate technical methods and results clearly in well structured reports and presentations to a range of technical and non-technical audiences