Data Analyst (Gamification CVM)

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics, and banking.   
 

Job Description: 

Fozzy Group is building a next-generation Customer Value Management (CVM) Decision Support System that  lives inside our app's gamified experience layer. Instead of traditional CRM triggers alone, engagement and retention are driven through game mechanics – achievement chains, progress bars, and personalized quests – and we need someone who can turn those mechanics into measurable, data-driven strategy. The project focuses on two major streams: 

• Engagement Growth: Driving gamification adoption, modeling guest lifecycle, and applying proactive strategies to increase purchase frequency and deepen engagement. 

• Retention & Loyalty Management: Early churn detection, loyalty preservation, and predictive modeling of customer attrition to implement timely and personalized interventions that reduce churn risk. 

You'll work closely with product, game-mechanic designers, CVM, and the wider Data Science team, and your models will directly shape decisions about quest design, reward economics, and lifecycle communication. 

Job Responsibilities 

• Model customer lifecycle stages inside the gamified platform – from first touch through onboarding to habitual engagement – and identifying where drop-off happens

• Design and A/B test game mechanics meant to convert guests into active app users (first-order quests, achievement chains, milestone rewards) 

• Automate customer targeting and personalized offer selection across CVM campaigns 

• Build next-best-quest / next-best-action logic to personalize each customer's path through the game 

• Design predictive triggers for retention interventions and measure whether they're actually incremental or just rewarding people who'd have stayed anyway 

• Build and maintain SQL pipelines to aggregate, clean, and transform customer and transactional data from multiple sources 

• Extensively utilize SQL and dbt to design, develop, and optimize data models within our high-volume data platform, effectively managing and processing multi-billion-row datasets 

• Develop data preparation pipelines and contribute to deploying ML models for churn prediction, segmentation, and uplift modeling. 
 

Requirements 

• Bachelor’s Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance 

• At least 2 years of working experience on Data Analytics 

• Strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques 

• Solid SQL and Python 

• Experience with BI tools (Power BI, Tableau, Looker) 

• Knowledge of statistical methods (Hypothesis testing, A/B tests, PCA) 

• Ability to work independently and structure complex problems into clear solutions. 
 

Preferred 

• Experience with Airflow, Docker, or Kubernetes for Data Orchestration 

• Spark/Trino and Lakehouse experience is a plus 

• Applied knowledge of Machine Learning (e.g., Decision Trees, Random Forest, and Boosting). 
 

What We Offer 

• Competitive salary; 

• Professional & personal development opportunities; 

• Being part of dynamic team of young & ambitious professionals; 

• Corporate discounts for sport clubs and language courses; 

• Medical insurance package.