Data Quality Analyst II
Varite
- Palo Alto, CA
- $30.00-40.00 per hour
- Permanent
- Full-time
Job title: Data Quality Analyst II
Location: Palo Alto CA
Duration: 09 months
Business Justification:
1. Label data for time-sensitive, business-critical projects.
2. Create evaluation data sets in conjunction with product engineering teams so researchers can develop their models with metrics that closely align with key business metrics.
3. Perform "human evaluation” and "red teaming” on our models in circumstances where automatic evaluation isn't yet development or not applicable.
4. Prototype new labeling tasks and data annotation techniques (e.g. synthetic data generation) prior to scaling them further with vendors or professional services. This will reduce the time to market for our AI-powered products and reduce costs by eliminating wastage from prematurely scaling new investments in data labeling.
5. Audit the quality of data from (1) third party vendors, e.g. and (2) client professional services. Verifying the quality of data prior to training our models is the responsibility of the AI research team.
Job Description:
Responsibilities:
- Accurately label machine learning data through various methods to refine AI models. This will primarily involve annotating large volumes of textual data according to predefined guidelines.
- Collaborate with team members to identify improvements to the labeling interface or labeling processes in order to drive efficiency and high-quality.
- Complete assignments by deadlines while meeting team expectations and goals.
- Bachelor's degree in English, Literature, Creative Writing, Journalism, or a related field (or equivalent work experience)
- Proficiency in reading comprehension and possessive of strong writing skills, with the ability to understand and interpret complex and diverse texts.
- Ability to work independently, follow instructions, manage time effectively, and meet deadlines in a dynamic and fast-paced environment.
- Ability to manage ambiguity, uncertainty, and changing priorities with limited resources.
- Ability to accept and integrate continuous feedback while remaining professional.
- Excellent verbal and written communication skills and the ability to collaborate within a multi-disciplinary team.
- Quick learner and self-starter with strong problem-solving skills.