Treasury Analytics Associate at Checkout.com
- Company: Checkout.com
- Location: Ebene
- Job type: full time
- Workplace: onsite
- Posted: 2026-06-02
Job description
Company Description We’re Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. We are seeking highly analytical and collaborative Associates with a focus on Treasury Analytics to join our growing global treasury function. Operating in a fast-paced payments environment, this role will serve as the technical engine for the Reporting and Analytics team. Reporting directly to the Manager, Enterprise Treasury, you will be responsible for executing technical data tasks, building scalable data models, and delivering high-quality, actionable reports that drive strategic decision-making across the various treasury functions. Because you will be working closely with cross-regional teams, the ability to translate complex technical concepts into clear business insights is critical. You will leverage modern data stacks to optimize reporting, while also having the exciting opportunity to explore and implement AI-driven analytics. Key Responsibilities: Communication & Stakeholder Management: • Act as the vital bridge between technical data architecture and business-focused enterprise treasury operations, translating complex data findings into clear, non-technical insights. • Proactively communicate with cross-regional teams (finance, engineering, and global treasury) across multiple time zones, ensuring alignment on data definitions, reporting requirements, and project timelines. • Draft clear, concise documentation for data pipelines, dashboard usage, and reporting metrics to ensure global teams can easily understand and leverage your tools. • Present analytical findings and AI/ML capabilities confidently to both the Manager and broader global stakeholders. Data Modeling & Technical Execution: • Take technical requirements translated by the Manager and develop robust data pipelines and models to support treasury operations. • Extract, transform, and load (ETL/ELT) complex datasets using modern tech stacks including dbt, Google BigQuery, and Snowflake. • Ensure data architecture is scalable, reliable, and optimized for rapid querying and analysis. Reporting, BI & Visualization: • Design, build, and maintain automated, user-friendly treasury dashboards and reports using Looker/Tableau/Power BI (or similar tools). • Ensure all reports are highly accurate, timely, and aligned with broader business OKRs. • Uncover and visualize key trends across all treasury domains to support senior stakeholders. AI & Advanced Analytics Initiatives: • Explore and implement AI, machine learning, and predictive analytics to improve treasury insights. • Drive continuous improvement by evaluating new tools and methodologies to keep the team’s tech stack at the cutting edge. Qualifications: • Education : Bachelor’s degree in Data Science, Computer Science, Mathematics, Finance, or a related quantitative field • Experience : • 2–4 years of experience in data analytics, data engineering, or business intelligence, preferably within a fintech, banking, payments, or financial services company. • Proven track record of working collaboratively and communicating effectively in distributed or cross-regional teams. • Technical Sk
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