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.