AI Data Quality Analyst — Human Data

Prolific; Mexico; Hybrid; PHP 420,000 - 720,000; Full time

Job summary

Prolific is seeking a Human Data Quality Analyst to ensure that data signals are valid and truly usable for training AI models. You will dig into datasets, identify patterns, and translate findings into practical recommendations.

You'll work closely with Quality, Engineering, Operations and Delivery, building data-quality pipelines and dashboards while learning fast in a rapidly evolving field of AI.

Qualifications

• 1–2 years of practical data analysis experience.
• Experience with SQL and Python for queries and analysis.
• Understanding of sampling, distributions, and variability.

Responsibilities

• Run day-to-day quality measurement across live human-data programmes, combining statistical analysis with regular hands-on review to determine whether the data is fit for its intended use.
• Find the signal behind quality issues by investigating changes, quantifying their impact and distinguishing individual errors from wider problems in guidance, task design, training or tooling.
• Help build the data-quality pipeline alongside our quality engineers, turning repeated analysis into reliable validations and automated systems, including rule-based, LLM, and ML assisted approaches.
• Turn complex analysis into a clear story through reporting and visualisations that help stakeholders understand what is happening, why it matters, and what action the evidence supports.
• Support new programmes from design through to launch by helping develop the rubrics, guidelines, gold sets, calibration exercises, and production gates to measure quality from the start.
• Use what we learn from live programmes to improve annotation design, guidance, training and quality processes, then measure whether those changes work.

Skills

Data analysis

Statistical thinking

Storytelling with data

Tools

SQL

Python

Job description

Prolific is seeking a Human Data Quality Analyst to ensure that data signals are valid and truly usable for training AI models. You will dig into datasets, identify patterns, and translate findings into practical recommendations.

You'll work closely with Quality, Engineering, Operations and Delivery, building data-quality pipelines and dashboards while learning fast in a rapidly evolving field of AI.