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About the Role
We are seeking a highly analytical and technically skilled Product Analyst to join our global team. This role is key to deepening our data capabilities, focusing on advanced analytics to shape the future of our payment products. The ideal candidate will bridge the gap between complex data infrastructure and actionable product strategy through expert data modeling, robust experimentation, and the development of machine learning classification models.
Responsibilities
- Design, implement, and analyze A/B and multivariate tests to optimize product features and drive conversion across both EU and US markets.
- Develop and maintain scalable data models within our data warehouse (e.g., dbt) to create single sources of truth for core product metrics.
- Build and deploy machine learning classification models (e.g., fraud detection, user segmentation) to enhance product quality and performance.
- Partner with Product Managers in the EU and US to define KPIs, prioritize features, and measure the impact of product launches.
- Conduct deep-dive analyses on complex product areas, translating findings into clear, persuasive recommendations for product improvements.
- Create and maintain automated dashboards and reports that provide real-time visibility into product health and user behavior.
- Collaborate with Data Engineering to ensure data quality, accessibility, and the implementation of proper tracking for new features.
- Educate and mentor product and business stakeholders on data interpretation and experimentation best practices.
- Leverage LLM agents and agentic analytics workflows to automate exploratory analysis, surface insights, and accelerate reporting across product lines.
Requirements
- 5+ years of experience as a Product Analyst, Data Scientist, or similar role, preferably in a FinTech or B2C/B2B SaaS environment.
- Expert proficiency in SQL for complex data manipulation and analysis is essential.
- Demonstrated experience in data modeling principles (e.g., Kimball, relational modeling) and using tools like dbt.
- Strong practical knowledge of designing and analyzing experiments (A/B testing) with a solid grasp of statistical inference.
- Hands-on experience building and deploying machine learning models (e.g., classification, clustering) using Python/R and relevant libraries (e.g., scikit-learn).
- Excellent ability to translate technical insights into clear, strategic business recommendations for non-technical audiences.
- Proven capacity to thrive in a fast-paced, global environment, managing competing priorities across different time zones (EU and US).
- Experience with BI tools like Looker, Tableau, or Power BI for dashboard development.
- Familiarity with LLM agents and agentic analytics tools (e.g., for automated data exploration, natural-language querying, or workflow orchestration) is a plus.
Skills
- SQL
- dbt
- A/B testing
- statistical inference
- Python
- R
- scikit-learn
- Looker
- Tableau
- Power BI
- LLM agents
- agentic analytics
Location
- EU
- US
Work Type
- global
Experience Level
- 5+ years
About the Company
- At Trustly, we're building a smarter, faster, and more secure financial future by revolutionizing the world of payments. As a global leader in Open Banking Payments, we are establishing Pay by Bank as the new standard at checkout, providing unparalleled freedom, speed, and ease to millions of consumers and merchants worldwide.
- Our Ambition: To build the world's most disruptive payment network and redefine what the payment experience should feel like.
- Trustly is a global team of innovators, collaborators, and doers. If you are driven by a strong sense of purpose and thrive in a dynamic, entrepreneurial, and high-growth environment, join us and be part of a team that's transforming the way the world pays.
Equal Opportunity
- At Trustly, we embrace and celebrate diversity of all forms and the value it brings to our employees and customers. We are proud and committed to being an Equal Opportunity Employer and believe an open and inclusive environment enables people to do their best work. All decisions regarding hiring, advancement, and any other aspects of employment are made solely on the basis of qualifications, merit, and business need.