Data Analyst

You will design dashboards, pipelines, and reports that reveal labeling throughput, QA patterns, and reviewer performance. You will quantify labeling effort and model-label performance, consolidate data from SQL, annotation tools, and audits, and provide actionable analysis to stakeholders to improve labeling accuracy and operational SLAs.

Responsibilities

• Design dashboards and reporting tools to track labeling throughput, SLA compliance, backlog dynamics, reviewer performance, and QA patterns
• Define and implement metrics to measure labeling quality, accuracy, efficiency, and cost
• Provide analytical support to ML Engineering, Product, and Sales/CS on labeling impact and operational SLAs
• Model labeling effort by quantifying task complexity, labeling speed, and reviewer dynamics
• Build and maintain data pipelines consolidating SQL, annotation tools, QA audits, and semi-structured feedback
• Translate operational data into accessible, reliable instrumentation for the labeling organization

Requirements

• 4–7 years of experience as a data analyst, business analyst, or ops analyst
• Strong SQL skills with experience in Redshift and joining large datasets
• Experience with dashboarding tools such as Tableau, Metabase, or Looker
• Working knowledge of Python for automation and data exploration
• Experience with labeling systems, QA pipelines, or operations metrics (preferred)
• Proven success owning end-to-end analytics cycles from question to impact
• Ability to translate complex systems into understandable views for diverse audiences

Benefits

• Flexible working hours and workplace
• Open vacation policy