Amazon Data Scientist III Customer Engagment Technologies 

United States, Washington, Seattle 

464519646

This involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities
1. Lead the development of LLM-based chatbots and conversational AI systems for customer service applications.
2. Implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation and dialogue quality assessment.4. Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.
5. Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.
A day in the life
Benefits Summary:1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

- 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
- 5+ years of data scientist experience
- Experience with unstructured textual data
- Experience working with scientists, economists, software developers, or product managers
- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science
- 5+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Experience applying theoretical models in an applied environment

- Knowledge of AWS tech stack (e.g., AWS Redshift, S3, EC2, Glue)
- Experience managing data pipelines
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer scienc