Senior product data scientist role focused on analyzing and improving ML system efficiency in a large-scale programmatic trading platform. Responsibilities include managing hardware unit costs, hunting inefficiencies in traffic and system setup, driving changes to implementation, launching and managing A/B tests, collaborating with Data Scientists on model performance data analysis, automating reports, and performing root-cause analysis on performance incidents. Requires strong SQL and Python skills, solid statistics and A/B testing knowledge, experience with BI and monitoring tools, 3+ years analytical experience with production-scale data, and fluency in English and Russian. The role is full-time, hybrid, located in Limassol, Cyprus or Yerevan, Armenia. Benefits include hybrid work model, career development, health and wellness support, diverse team, competitive salary with performance rewards, and potential equity.
Hunt inefficiencies in traffic and system setup including bidstream management, supply path optimization, duplication/multisize handling, latency tuning
Drive findings from detection to executed change and measure financial impact
Launch and manage A/B tests from design to verdict to validate changes
Collaborate with Data Scientists on model performance investigations focusing on data side
Analyze performance at granular partner and segment levels
Analyze cross-component inefficiencies and trading-pair performance
Automate recurring manual checks into reports and tooling
Perform root-cause analysis on incidents affecting performance or margin
Work closely with Data Scientists, R&D, Product, TAM, and Client Services to provide evidence-backed answers and insights
Communicate findings clearly to technical and non-technical audiences
Requirements
Bias to implementation: satisfaction from initiatives that reach production and generate or save money
Proactive ownership: ability to notice issues first and convince others to act
Critical thinking: validate data sources, assumptions, and AI outputs
Strong communication and relationship building across teams
Confident SQL skills with window functions and aggregation on TB-scale event logs
Python skills including pandas, numpy, and visualization
Solid grasp of statistics and A/B testing fundamentals
Working understanding of ML metrics and model behavior for monitoring and debugging
Experience with BI and monitoring tools (Grafana, Tableau, Superset, or similar)
3+ years of hands-on analytical experience with production-scale data
Hybrid work model blending home and in-office experiencesLearning, mentorship, and career development programsHealth benefits, wellness perks, and mental health supportDiverse, inclusive, and globally connected teamAttractive salary with performance-based rewards and family-friendly policiesPotential for equity depending on role and level
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