Language Data Scientist, Alexa International Tech

- 2+ years of data scientist experience
- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 3+ 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
- Experience in Python, Perl, or another scripting language
- Experience in a ML or data scientist role with a large technology company
- Master's degree, or PhD

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 $125,500/year in our lowest geographic market up to $212,800/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.
Alexa International Tech (AIT) team is looking for a passionate, talented, and inventive Sr language Data Scientist to help build industry-leading technology with Large Language Models (LLMs) and multimodal systems, requiring strong deep learning and generative models knowledge.

You will collaborate with fellow Language Data Scientists, Program managers, as well as Stakeholders in science, engineering, and product teams to understand the role data plays in developing data sets and exemplars that meet customer needs. You will analyze and automate processes for collecting and annotating LLM inputs and outputs to assess data quality and measurement.
You will apply state-of-the-art Generative AI techniques to analyze how well our data represents human language and run experiments to gauge downstream interactions. You will work collaboratively with other language data scientists and scientists to design and implement principled strategies for data optimization.




Key job responsibilities
Collaborate with Scientists and Software Engineers to help design APIs and evaluate performance of LLM

Produce and manipulate different types of language data, analyze, and provide efficient solutions

Design and lead a data collection; define scope and target, provide a guideline and training, guide teams cross sites to meet the quality bar, and run evaluation of data for hand off

Engineer prompts to guide generative AI to produce desired outputs in context

Automate operations and perform data analysis using python, or other scripting language.

Advocate strict adherence to annotation guidelines
Test and deploy changes to Alexa's language understanding codebase

Identify and solve production issues that are impacting the Alexa customer experience,

Collaborate with other linguists, scientists and designers in creating optimal solutions to elevate the customer experience

Own the customer-facing machine learning and deterministic models for a specific domain of features

Use modeling tools to bootstrap and test new functionalities