Senior Data Analyst

OnTheGoSystems is a remote team of tech enthusiasts, innovators, creatives, and engineers. We work together to harness the power of translation technologies and allow businesses of all sizes to go global. From algorithms and AI to machine learning, we create cutting-edge, affordable tools that make an impact.

• Strong analytical thinking, curiosity, and attention to detail.
• Ability to work independently and define what should be investigated.
• Experience turning open-ended questions into structured analyses and actionable recommendations.
• 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 ability to explain analytical findings to non-technical colleagues.

Nice to have:

• Experience with translation quality or localization.
• Experience with multilingual content.
• Experience with data visualization or business intelligence tools.

• Own analytical problems from start to finish.
• Define meaningful metrics for translation quality, AI performance, and user behavior.
• Monitor trends and identify unusual patterns or quality issues.
• Turn observations into structured investigations and test multiple hypotheses.
• Extract and combine data from SQL databases, NoSQL databases, logs, APIs, and CSV exports.
• Compare results across language pairs, AI models, providers, customers, content types, traffic levels, and other dimensions.
• Separate real signals from coincidence by validating findings with data.
• Review translation samples to confirm whether patterns represent genuine quality issues.
• Investigate root causes and recommend practical improvements.
• Evaluate multilingual AI output for meaning, terminology, tone, formality, grammar, pronouns, and consistency.
• Use AI tools, dictionaries, and other resources to investigate languages you don't speak.
• Review AI-generated analyses, identify incorrect conclusions, and help improve automated evaluation systems.
• Build repeatable reports, scripts, and monitoring processes.
• Communicate findings clearly to developers, product managers, and linguists.