We are a leading trading platform that is ambitiously expanding to the four corners of the globe. Our top-rated products have won prestigious industry awards for their cutting-edge technology and seamless client experience. We deliver only the best, so we are always in search of the best people to join our ever-growing talented team.
We are looking for a Marketing Analyst to join our Marketing Intelligence & Automation team in Warsaw. Our marketing team already uses an AI-powered decision system to recommend where budget should go. What limits it today is measurement: the sharper our attribution, marketing mix models and experiments, the more decisions we can trust it to make. Your job is to strengthen that foundation and turn marketing data into insights that change how we invest.
Responsibilities:
Build, maintain and improve attribution models, and support new attribution model releases.
Develop and refine marketing mix models (MMM) to understand channel contribution and guide budget allocation.
Design and analyze incrementality tests and experiments to measure the true impact of marketing activity.
Deliver regular reporting and deep-dive analysis on channel, campaign and user performance across markets.
Turn findings into clear, actionable recommendations for marketing stakeholders, linked to acquisition cost, client value and revenue.
Define and document marketing metrics and KPIs so the team works from one source of truth.
Improve the measurement inputs that feed our AI-driven budget recommendation and automation systems.
Partner with MarTech, analytics engineering and, increasingly, Product Marketing and CRM teams on shared measurement needs.
Requirements:
3–5 years of experience in marketing analytics, growth analytics or a similar role.
Experience in financial services, such as trading, brokerage, fintech or banking is a must.
Hands-on experience with attribution modeling and/or marketing mix modeling.
Strong SQL skills and experience working with large marketing datasets.
Solid understanding of statistics and experimentation, including incrementality testing.
Strong critical thinking: you structure ambiguous problems, challenge assumptions and connect analysis to business impact.
Ability to explain complex findings clearly to non-technical stakeholders.
Nice to have:
Python (or R) for analysis and modeling.
Hands-on experience with Tableau (or a similar BI tool) and analytics platforms like Google Analytics 4.
Experience using AI tools or LLMs for analysis or workflow automation, at work or in your own projects.
