Product / Data Analyst (DSP and Big Data)

About the Role

We are looking for a mature Product / Data Analyst who will become the absolute owner of our data tracking and analytics ecosystem.

This is a "Greenfield" opportunity to build analytics layer for Big Data B2B SaaS product  while extracting deep mathematical insights from raw Big Data to optimize our retargeting algorithms.

Responsibilities

• Build BI Infrastructure from Scratch: Evaluate and select the optimal BI tool (Looker Studio, Grafana, Apache Superset, or Metabase) over our ClickHouse database to eliminate manual report-building.
• Behavioral & Touchpoint Analysis: Model Path to Conversion, optimize Frequency Caps, and run Recency & Frequency analysis to find "golden hours" and maximize conversion probability.
• Incrementality & Attribution: Mathematically prove incremental GGR uplift and measure the indirect impact of ad contacts (post-view effects) through control groups.
• Data Quality & Logging: Control metadata collection integrity (IP, User-Agent, Device ID) and formulate requirements for logging new data points.
• Big Data & Query Optimization: Independently write and optimize complex SQL queries in ClickHouse to process billions of raw events without relying on the engineering team.
• Product Insights: Utilize Python for cohort analysis, target audience segmentation in a Cookieless environment, and pattern detection for anti-fraud.

Who We’re Looking For

We’re looking for a mature, self-driven analyst who loves data engineering challenges, possesses strong mathematical logic, and can translate raw numbers into business impact.

Must-have:

• 3+ years of commercial experience in data/product analytics working with Big Data.
• Strong domain expertise: Experience in high-load industries such as AdTech, RTB, MarTech, or iGaming.
• Advanced SQL (ClickHouse): Deep understanding of column-oriented databases and raw log processing.
• Python Proficiency: Strong practical experience with Pandas and NumPy for complex cohort and statistical analysis.
• Data Visualization Mastery: Confident experience designing and connecting BI dashboards completely from scratch.
• English: Intermediate or higher (comfortable reading technical documentation and product contexts).
• Ukrainian/Russian: Fluent (for internal team communication).

Nice to have:

• Academic background in Mathematics, Statistics, Data Analysis, or Probability Theory.
• Experience in anti-fraud traffic analytics.
• Understanding of subscription models and LTV forecasting.

How We Work

• Direct reporting line to the Product Owner / CEO.
• Focus on automated, long-term infrastructure over routine daily manual exports.
• Full autonomy in selecting data-analysis tools.
• Clear boundaries: The analyst does not manage ad campaigns manually and does not act as a database administrator (DBA).

What We Offer

• Full ownership over the company's data architecture and reporting standards.
• A highly complex, high-load product dealing with billions of events.
• Competitive compensation.
• 100% remote format with international market exposure.

Role Summary

The Product / Data Analyst is responsible for transforming raw ClickHouse logs into a transparent, automated BI ecosystem while delivering mathematically sound insights to boost the platform's retargeting efficiency.