Sr Data Scientist, Health & Wellness (Health Tech)

- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $143,300/year in our lowest geographic market up to $247,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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.