Data Analyst

What you'll do

You'll own analytical problems from start to finish.

For example, you may discover that users edit translations much more often for one language pair than another. Instead of simply reporting it, you'll investigate why. You'll form hypotheses, gather the data, test possible explanations, and recommend the next steps.

Your work will include:

• Defining meaningful metrics for translation quality, AI performance, and user behavior.
• Monitoring trends and identifying unusual patterns or quality issues.
• Turning observations into structured investigations and testing multiple hypotheses.
• Extracting and combining data from SQL databases, NoSQL databases, logs, APIs, and CSV exports.
• Comparing results across language pairs, AI models, providers, customers, content types, traffic levels, and other dimensions.
• Separating real signals from coincidence by validating findings with data.
• Reviewing translation samples to confirm whether patterns represent genuine quality issues.
• Investigating root causes and recommending practical improvements.
• Evaluating multilingual AI output for meaning, terminology, tone, formality, grammar, pronouns, and consistency.
• Using AI tools, dictionaries, and other resources to investigate languages you don't speak, while recognizing when expert linguistic input is needed.
• Reviewing AI-generated analyses, identifying incorrect conclusions, and helping improve our automated evaluation systems.
• Building repeatable reports, scripts, and monitoring processes.
• Communicating findings clearly to developers, product managers, and linguists.

Requirements

• Strong analytical thinking, curiosity, and attention to detail.
• The ability to work independently and define what should be investigated.
• Experience turning open-ended questions into structured analyses and actionable recommendations.
• A solid understanding of metrics, segmentation, distributions, correlations, and the difference between correlation and causation.
• Experience writing SQL, Python, or similar scripts to collect, clean, and analyze data.
• Experience working with multiple data sources, including databases, logs, APIs, and exported datasets.
• Strong hands-on experience using AI tools while critically evaluating their output.
• Fluent English plus at least one additional language (preferably European), with the ability to assess translation quality and explain language issues.
• Clear written communication and the ability to explain analytical findings to non-technical colleagues.

Bonus points for experience with:

• Translation quality or localization.
• Multilingual content.
• Data visualization or business intelligence tools.

Benefits

You'll work on real AI systems used by customers around the world and directly influence how we measure and improve machine translation quality.

This role is ideal for someone who enjoys exploring difficult questions, testing ideas, and discovering insights that aren't immediately obvious. You'll have the freedom to propose your own analyses and the responsibility to turn them into evidence-based recommendations.