At a Glance
- Tasks: Analyse payments data and deliver actionable insights to optimise business performance.
- Company: Join Teya, a dynamic payment and software service provider in London.
- Benefits: Enjoy health support, generous leave, and a friendly office vibe.
- Other info: Inclusive workplace committed to diversity and personal growth.
- Why this job: Make a real impact on local businesses while working with cutting-edge data tools.
- Qualifications: 2+ years in Data Analytics, strong SQL skills, and a passion for payments.
The predicted salary is between 45000 - 55000 £ per year.
We’re Teya, a payment and software service provider headquartered in London serving small, local businesses across Europe. Founded in 2019, we build easy‑to‑use, integrated tools that enable our members to accept payments and boost business performance. We’re looking for a Payments Data Analyst to join our London team. You will take ownership of the payments data layer, working at the intersection of Product, Commercial, and Engineering to ensure our acquiring business is measurable, scalable, and optimized for performance.
Your Responsibilities
- Act as the subject matter expert for the payments data lifecycle, covering authorisation, clearing, settlement, and reconciliation.
- Go beyond standard reporting by delivering unprompted insights.
- Diagnose root causes of changes in authorisation rates and identify margin leakage driven by transaction mix or fee structures.
- Work closely with Product Managers to define success metrics for new features and support Commercial teams with merchant‑level profitability analysis and pricing scenarios.
- Own the “single source of truth” for key payments metrics (volumes, revenue, margins).
- Collaborate with Engineering to define tracking requirements and proactively identify and resolve data gaps.
- Build and maintain a robust semantic layer on top of payments data, ensuring consistent metric definitions across the business and enabling AI‑driven workflows and Snowflake Cortex use cases.
- Develop scalable data models in dbt and create Tableau dashboards that empower stakeholders to self‑serve insights, while you focus on deeper strategic analysis.
- Translate complex terminal, POS, and eCommerce data into clear, actionable insights for senior stakeholders to inform product roadmap and pricing decisions.
Must Have
- 2+ years of experience in a Data Analytics role within Payments, Acquiring, or FinTech.
- Strong understanding of the card transaction lifecycle (Authorisation, Clearing, Settlement).
- Familiarity with fee structures (Interchange, Scheme Fees, Blended vs IC+ pricing).
- Strong proficiency in SQL and Tableau (or equivalent BI tool).
- Hands‑on experience with dbt and data modelling.
- Familiarity with Git and cloud data environments (e.g., Snowflake, AWS).
- Strong analytical mindset with a focus on root cause analysis and experimentation.
- Excellent communication skills with the ability to influence cross‑functional stakeholders.
Nice to Have
- Experience working with Card‑Present / POS terminal data.
- Knowledge of chargebacks and dispute processes.
- Proficiency in Python for modelling or advanced analysis.
- Experience with pricing optimisation or portfolio segmentation.
- Exposure to international payment schemes and local payment methods.
The Perks
- Physical and mental health support through our partnership with GymPass, including access to gyms, therapy, meditation, and wellness apps.
- Enhanced maternity and paternity leave policies.
- Cycle‑to‑Work Scheme.
- Private Health and Life Insurance.
- Pension Scheme.
- 25 days annual leave + bank holidays.
- Daily office snacks.
- Friendly, collaborative, and informal office environment in Central London.
Teya is proud to be an equal opportunity employer. We are committed to creating an inclusive environment where everyone, regardless of race, ethnicity, gender identity or expression, sexual orientation, age, disability, religion, or background, can thrive and do their best work. We believe that a diverse team leads to better ideas, stronger outcomes, and a more supportive workplace for all. If you require any reasonable adjustments at any stage of the recruitment process whether for interviews, assessments, or other parts of the application—we encourage you to let us know. We are committed to ensuring that every candidate has a fair and accessible experience with us.
Data Analyst (Payments) employer: Teya
At Teya, we pride ourselves on being an exceptional employer, offering a vibrant and inclusive work culture in the heart of Central London. Our commitment to employee well-being is reflected in our comprehensive benefits package, including health support through GymPass, generous parental leave, and a collaborative office environment that fosters growth and innovation. Join us as a Payments Data Analyst and take advantage of unique opportunities for professional development while contributing to meaningful projects that empower small businesses across Europe.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst (Payments)
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We think you need these skills to ace Data Analyst (Payments)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Teya
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.