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Key job responsibilities
Attention to detail (linguistically and culturally)
Strong grammar skills
Critical thinking and analytical skills when it comes to evaluating linguistic data (ask questions)
Ability to identify potential biases (and be aware of your own biases)
Sufficient annotator experience to identify when there is a major issue with the task that should be escalated
Experience in some specific domains, like healthcare, finance, retail, etc
Having strong writing/communication skills to communicate with stakeholders.
Quality assurance experience
Good research and reading comprehension skills.
Willing to work round in PST timezone.A day in the life
We are looking for a Data Associate (DA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech & text data, to assess and improve performance in everyday situations.
To make a mark, one needs to be an expert, your adaptability, focus, and attention to detail in a dynamic need to be unparalleled. To pride yourself on your ability to recognize issues, not succumb to pressure, but come up with an elegant and innovative solution to tackle any hurdle from the goal while working on multi-data modalities.About the team
Diverse Experiences
AWS 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.Mentorship & 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.Work/Life Balance
- Bachelor's degree
- Knowledge of Microsoft Office products and applications
- Speak, write, and read fluently in English
- Bachelor's degree in a relevant field, such as Linguistics, Communications, a foreign language, or other language or data-related disciplines, including teaching.
- Experience with natural language data labeling, data annotation, linguistic annotation or other forms of data markup.
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