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Jobs / Checkout.com

Associate, Finance Analytics

Checkout.com·Londonmid

In short

  • →Analista financiero con enfoque en datos, apoyando operaciones de tesorería global.
  • →Crea pipelines de datos, dashboards y versiones predictivas usando BigQuery, dbt y Looker.
  • →Destacado por integrar inteligencia artificial y machine learning en análisis financieros.

Inglés avanzado requerido para comunicación con equipos globales.

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The questions they'll ask you

1. ¿Cómo has usado dbt para transformar datos en un pipeline de ETL real?

2. Describe un caso donde diste a un stakeholder no técnico una explicación clara de un hallazgo complejo.

3. ¿Qué ventajas has visto en usar AI/ML para prever flujos de caja en tesorería?

🔒 +7 more questions

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💵 USD · Remote · No visa

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What they ask for

  • ✓Experiencia de 2–4 años en análisis de datos, ingeniería de datos o BI.
  • ✓Dominio avanzado de SQL y warehousing en BigQuery y Snowflake.
  • ✓Experiencia práctica con dbt para transformación de datos.
  • ✓Capacidad para construir dashboards con Looker, Tableau o Power BI.
  • ✓Habilidades excepcionales de comunicación con equipos globales.
  • ✓Formación en Ciencias de Datos, Matemáticas, Finanzas o campo cuantitativo.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

SQLBigQuerySnowflakedbtLookerTableauPower BIPythonRAI/ML

Who should you write to at Checkout.com?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

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. 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 (Not Mandatory). 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 Skills : Advanced proficiency in SQL and cloud data warehousing (specifically BigQuery and Snowflake ). Hands-on experience with data transformation tools ( dbt ). Strong expertise in building dashboards and visualizations in Looker . Bonus : Practical experience or strong familiarity with integrating AI/ML models or leveraging Python/R for predictive analytics. Key Competencies: Exceptional Communicator: Strong written and verbal communication skills; able to distill complex, technical data into clear narratives for diverse, global audiences. Technical Agility: Deep understanding of the modern big data tech stack with an appetite for adopting new technologies, particularly in the AI space. Collaboration & Teamwork: Thrives in a globally distributed environment, working seamlessly with diverse teams across borders and cultures.

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