Performance Analyst​/Marketing Analytics Specialist

Overview

We are a growth team responsible for the growth of the company. We are looking for a Performance Analyst who will own event tracking, attribution quality, and traffic efficiency across mobile and web products.

• Implement and maintain event tracking for mobile apps and web platforms.
• Work with 3rd-party tracking platforms (Adjust, Apps Flyer).
• Postback setup and reconciliation.
• Integrate and support SDKs (mobile & web) in close collaboration with engineering teams.
• Work with Google Firebase: event configuration and validation funnel, retention, and behavioral analysis.
• Work with Google ICM and Facebook AEM.
• Design and maintain server-to-server (S2S) tracking: client vs server-side event logic.
• Monitoring and resolving data discrepancies.
• Analyze traffic quality and data efficiency.
• Identify low-quality or fraudulent traffic.
• Analyze cohort behavior, retention, LTV, and conversion paths.
• Apply anti-fraud techniques:
• Detect abnormal patterns (click spamming, SDK spoofing, bot traffic, attribution fraud).
• Collaborate with platforms and ad networks on fraud prevention.
• Build and maintain whitelists and blacklists of traffic sources, placements, and publishers.
• Design and maintain dashboards and performance reports for marketing and business teams.
• Develop forecasting and predictive models:
• Traffic and revenue forecasting.
• LTV and cohort-based predictions.
• Support experimentation and A/B testing (analysis and conclusions).

• Must-have:
• 3+ years of experience in performance, mobile, or product analytics.
• Strong understanding of:
• Event-based analytics.
• Attribution models.
• Client-side vs S2S tracking.
• Traffic quality metrics and fraud patterns.
• Hands-on experience with:
• Appsflyer and/or Adjust.
• Google Firebase.
• SDK integrations.
• SQL skills and experience working with raw data.
• Experience collaborating with developers and marketing teams.

• Experience with BI tools (Looker, Tableau, Power BI, etc.).
• Experience with anti-fraud tools and methodologies.
• Knowledge of GA4.
• Experience with CDP, DWH, or data pipelines.
• Basic experience with statistical modeling or machine learning.

• Professional growth: support for courses, conferences, and English learning (up to 100% coverage).
• Work-life fit: remote or hybrid format with flexible hours across international teams.
• Paid leave: up to 28 vacation days, 15 sick days, plus local holidays.
• Recognition programs: structured performance reviews and team awards.
• Team culture: retreats in international locations (for example, company villa in Turkey, Bali).