Minimum qualifications:
- Bachelor's degree with coursework of a quantitative nature (e.g., Economics, Engineering, Computer Science, Finance, Management) or equivalent practical experience.
- 5 years of experience working with databases and querying (e.g., SQL, MySQL, MapReduce, Hadoop).
- Experience with statistical concepts and analysis.
- Experience with data representation and dashboards.
- Master's degree in Statistics, Math, Physics, Economics, or a related field.
- Experience with checking and reviewing code.
- Experience with developing and maintaining machine learning models.
- Ability to communicate and influence executive leadership by creating insights from data and presenting clear recommendations.
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About the job
In Trust and Safety Scaled Operations Quality, our mission is to set the gold standard for quality assurance in the trust and safety industry.
Trust and Safety extended workforce of manual reviewers is the largest in the fraud, spam, abuse, and content moderation industry. Establishing trusted and proven quality assurance standards for the work of our extended workforce is critical, as incorrect decisions made by manual reviewers can have significant implications on users and/or on machine learning models which consume the labels produced in the manual review process.
As a team, we define how to measure the quality of manual reviews, build monitoring tools and processes for the same, and ensure that emerging quality issues are detected in a timely manner. When quality issues surface, we initiate and facilitate root cause and corrective action analyses. We represent Trust and Safety in front of cross-functional partners, to build transparency around and trust in our quality management processes.
As a Technical Analyst, you will have the opportunity to influence the Trust and Safety approach to quality assurance. Your focus will be on bringing statistical excellence to the work we do and ensuring that we build a robust and scalable framework. In addition, you will be evolving the use of all the data at our disposal, setting the Trust and Safety industry standard for how to leverage data in the context of quality assurance.
Responsibilities
- Design sampling and data infrastructure for scalability. Influence how data is structured and stored, to enable fast and seamless insights generation across one of the industry's largest extended workforces.
- Design and build the metrics and monitoring tools required to proactively detect any quality-related issues. Own quality metrics definitions and ensure that these are statistically and methodologically consistent. Develop statistically thoroughsampling strategies.
- Leverage the wealth of data generated by the above (e.g., by performing causal analyses, quantifying impact of corrective actions implemented, understanding the relationship between quality, and other business metrics).
- Leverage modeling and machine learning techniques to develop and maintain a portfolio of models to identify reviewer errors.