Amazon Language Data Scientist III AWS Q Business 

United States, California 

154105584

Key job responsibilities
* oversee end-to-end evaluation data pipeline and propose evaluation metrics and methods
* incorporate your knowledge of linguistic fundamentals, NLU, NLP to the data pipeline
* process and analyze diverse media formats including audio recordings, video, images and text
* perform statistical analysis of the data
* write intuitive data generation & annotation guidelines
* write advanced and nuanced prompts to optimize LLM outputs
* write python scripts for data wrangling
* automate repetitive workflows and improve existing processes
* perform background research and vet available public datasets on topics such as long text retrieval, text generation, summarization, question-answering, and reasoning
* leverage and integrate AWS services to optimize data collection workflows
* collaborate with scientists, engineers, and product managers in defining data quality metrics and guidelines.
* lead dive deep sessions with data annotatorsUtility Computing (UC)Work/Life Balance
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

- 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
- Excellent knowledge of semantics, pragmatics, conversation analysis, and/or discourse analysis
- Experience designing and executing data collection projects, including guidelines, labelset and annotation workflow development
- Experience developing and evaluating data annotation and data quality metrics

- 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