AI Product Analyst

New
Serbia, CET-overlapping hoursFull-TimeMiddle
Salary not disclosed
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Job Details

Languages
Russian, English
Experience
3+ years
Required Skills
PythonSQLData AnalysisMachine LearningLLMLangChain

Requirements

  • 3+ years of experience in analytical roles related to AI systems, ML products, automation platforms, or complex production systems
  • Strong Python skills for deep analytical investigations and working with large-scale noisy text data
  • Advanced SQL skills
  • Understanding of LLM limitations, hallucinations, evaluation challenges, prompt sensitivity, model trade-offs, and AI failure modes
  • Experience building monitoring systems, analytical frameworks, or operational dashboards for production systems
  • Ability to work with incomplete, ambiguous, and rapidly changing data environments
  • Strong ownership mindset and ability to independently drive investigations and analytical conclusions
  • Ability to connect AI system quality with business and operational impact
  • Fluent Russian; English level B2 or higher
  • Ability to work CET-overlapping hours

Responsibilities

  • Analyze production behavior of AI agents, automation systems, and LLM-powered workflows
  • Investigate hallucinations, inconsistencies, failure modes, and quality degradation across automated user journeys
  • Work directly with logs, conversations, raw system outputs, and operational datasets to identify hidden patterns and actionable insights
  • Design evaluation approaches and analytical frameworks for measuring AI system quality and reliability
  • Build monitoring systems and dashboards for AI performance visibility
  • Identify operational and product risks introduced by automation
  • Measure the impact of AI systems on business metrics, operational efficiency, and user experience
  • Detect data quality issues, shifts, and anomalies affecting AI system performance
  • Partner closely with Product, Engineering, QA, and Operations teams on AI-related initiatives
  • Support rapid decision-making in fast-changing and ambiguous environments
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