Machine Learning Data Analyst

TL;DR

Machine Learning Data Analyst: Design and maintain automated data pipelines and quality standards to support ML model training and evaluation with an accent on data accuracy, workflow orchestration, and scalable performance tracking. Focus on building reliable systems for data labeling, metric computation, and collaboration with ML engineers to ensure high-quality document intelligence solutions.

Location: Remote, open to global candidates

Company

hirify.global is a Series B unicorn providing AI-powered identity verification solutions used by major enterprises worldwide, including banks, fintechs, and governments.

What you will do

• Design, build, and maintain automated data pipelines for ML training, labeling, validation, and metric computation.
• Establish and monitor data and labeling quality standards, perform audits and root-cause analysis.
• Implement and automate model evaluation metrics and reporting aligned with business goals.
• Build scalable systems for performance tracking, dashboards, and monitoring to enable data-driven decisions.
• Develop and operate workflow orchestration tools like Airflow or Prefect for end-to-end pipeline management.
• Collaborate closely with ML engineers, analysts, and product stakeholders to prioritize and improve tooling.

Requirements

• Must have 3+ years experience as a Data Analyst or similar data infrastructure role.
• Strong Python programming and SQL skills with experience in cloud or columnar databases (AWS Redshift).
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster).
• Proven experience in data quality management, data preparation, and ML data pipelines.
• Background in mathematics, physics, or engineering.
• English proficiency at least B2 level.

Nice to have

• Experience with big data technologies and data infrastructure optimization.
• Familiarity with labeling workflows and ML data preparation pipelines.
• Exposure to AWS or other cloud-based data solutions.
• Interest in machine learning operations (MLOps) and scalable ML systems.

Culture & Benefits

• Flexible working hours and workplace with open vacation policy.
• High performance culture with freedom and responsibility.
• Continuous feedback and promotion opportunities.
• Global impact working with AI-powered identity verification systems.