Amazon

Sr Data Scientist, Health & Wellness (Health Tech)

US, WA, Seattle
31 days ago

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This is a unique opportunity to join a small, high-impact team working on AI agents for health initiatives. You will lead the crucial data foundation of our project, managing health data acquisition, processing, and model evaluation, while also contributing to machine learning model development. Your work will directly influence the creation and improvement of AI solutions that could significantly impact how individuals manage their daily health and long-term wellness goals.

If you're passionate about leveraging data and developing ML models to solve meaningful problems in healthcare through AI, this role is for you. You'll work on large-scale data processing, design annotation workflows, develop evaluation metrics, and contribute to the machine learning algorithms that drive the performance of our health AI agents. You'll have the chance to innovate alongside healthcare experts and data scientists.

In this early-stage initiative, you'll have significant influence on our data strategies and ML approaches, shaping how they drive our AI solutions. This is an excellent opportunity for a high-judgment data scientist with ML expertise to demonstrate impact and make key decisions that will form the backbone of our health AI initiatives.


Key job responsibilities
Be the complete owner for health data acquisition, processing, and quality assurance
Design and oversee data annotation workflows
Collaborate on data sourcing strategies
Lead health data acquisition and processing initiatives
Manage AI agent example annotation processes
Develop and implement data evaluation metrics
Design, implement, and evaluate machine learning models for AI agents, with a focus on improving natural language understanding and generation in health contexts


A day in the life
You'll work with a cross-disciplinary team to source, evaluate, and leverage health data for AI agent development. You'll shape data acquisition strategies, annotation workflows, and machine learning models to enhance our AI's health knowledge. Expect to dive deep into complex health datasets, challenge conventional data evaluation metrics, and continuously refine our AI agents' ability to understand and respond to health-related queries.

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