Associate, Finance Analytics
Checkout.com is hiring an Associate, Finance Analytics in London, United Kingdom. Level rates it ; you can apply on Level.
Level's read on this job
- Little AI ●○○○ is how Level rates this finance role: aI is not part of the work.
- The posting mentions dbt, Google Bigquery and Snowflake among its tools and skills.
- Level classes it as a mid-level role.
- Checkout.com has 168 other open roles on Level.
- This posting went up within the past week.
AI in this role
Builds data pipelines, treasury dashboards, and financial models while exploring AI and machine learning initiatives.
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.
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 (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.
Analytical Problem-Solving: Highly skilled at diving into complex, messy data to extract clean, reliable, and actionable insights.
Execution-Oriented: Ability to take high-level objectives and technical tasks delegated by the Manager and deliver scalable solutions efficiently.
Additional Information
Bring all of you to work
We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one.
Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands.
We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here.
It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable.
Life at Checkout.com
We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection.
Curious about what it’s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us.
For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram
How we rate this
Associate, Finance Analytics at Checkout.com rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in finance jobs at this level
Pay
- Typical finance job
- $106k
This posting doesn't list pay. Use the typical finance figure when pay comes up. See finance jobs
Questions you could be asked
- Tell me about a project where data modeling was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where financial analytics was part of your work. What did you do?
- Tell me about a project where treasury operations was part of your work. What did you do?
- Tell me about a project where stakeholder management was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Data Modeling, ETL, Financial Analytics, Treasury Operations, and Stakeholder Management. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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