Credit risk data analyst in BNPL

Scalapay S.R.L.; Barcelona; On-site; EUR 32,000 - 44,000; Full time

Benefits offered by this job

Competitive salary

Barcelona office

Job summary

Scalapay S.R.L. in Barcelona is seeking a Credit Risk Data Analyst to join the team and shape credit decisions across a growing European portfolio. You will work closely with risk, data, and commercial teams to translate analysis into production-ready decisions.

You will own the credit strategy, build monitoring, and collaborate on models and pipelines with Data Science and Data Engineering, driving risk-adjusted profitability and portfolio performance.

Qualifications

• Degree in a quantitative field or equivalent demonstrated quantitative ability.
• 3+ years in an analytical role where your output drove decisions.
• Strong SQL with complex joins and window functions.
• Some exposure to Python, reading pandas scripts and adapting them.
• Fluent English (B2+ level).

Responsibilities

• Manage the credit strategy for a consumer portfolio across Europe and merchants.
• Collaborate with Commercial and Account Management to align risk appetite and growth.
• Review merchants and segments, decide portfolio adjustments and implement.
• Take credit decisions from analysis to production.
• Propose, size, test, and ship changes to rules, limits and thresholds.
• Build monitoring to measure risk-adjusted profitability and portfolio performance.
• Work with Data Science and Data Engineering on models and data pipelines for decisions.

Skills

SQL

Python

Proactivity

Communication

Query understanding

Education

Quantitative degree

Tools

Git

CI/CD

dbt

Job description

Behind every purchase paid in installments at one of our merchants there is a credit decision we make and own. The Credit Risk team is responsible for those decisions: who we approve, how much we extend, on what terms, and how the portfolio performs afterwards. We're looking for a Credit Risk Data Analyst to join the team in Barcelona. The portfolio we manage is growing, BNPL is coming into the European regulatory perimeter, and we're building the team and the tooling to match.

Задачи:

• Manage the credit strategy of a consumer portfolio built on millions of customers and thousands of merchants across multiple European countries: how much we extend, to whom and through which merchants.
• You'll work with Commercial and Account Management so that risk appetite and growth pull in the same direction.
• Review merchants and segments, decide where the portfolio should be adjusted, and make it happen.
• Take credit decisions from analysis to production.
• Rules, credit limits, thresholds: propose the change, size it, test it, ship it, and measure what happened.
• You take the decisions, not only prepare them. You'll hold a clear mandate on merchant and portfolio decisions from the start, with the team behind you and room to grow it.
• Build the monitoring that tells us whether the portfolio and our decisions are doing what we expect, with risk-adjusted profitability as the organising metric.
• Monitor the portfolio across customers, merchants and countries, and dig into what's moving before it turns into losses.
• Build the team's knowledge base as you go: the decisions we take, the changes we ship and the reasoning behind them.
• Work with Data Science and Data Engineering on the models, features, pipelines and data that feed our decisions.
• We're aiming for a self-sufficient team on the data stack.
• Work with the rest of the Risk function, Fraud included, on the patterns that drive losses and what to do about them.
• As you settle in, you'll take on a project of your own end to end.

Требования:

• A degree in engineering, physics, computer science, mathematics, statistics, economics or another quantitative field, or equivalent demonstrated quantitative ability.
• 3+ years in an analytical role where your output drove decisions.
• Strong SQL. You use it every day, you're comfortable with complex joins and window functions, and you can read someone else's query and work out why two numbers disagree.
• Some exposure to Python, at work or in your own projects. You can read a pandas script and adapt it to get to a result.
• You don't need to be a software engineer.
• Proactivity and technical curiosity. Our domain is technical: decisions live in code, configs and pipelines, and the people who do well here go and look at how things work rather than waiting to be told.
• Clear communication. You can explain a complex analysis to different audiences, from Commercial to leadership, and you can stand behind your conclusions.
• Fluent English (B2+ level). We use it on a daily basis and this is our global internal language.
• Будет плюсом: Exposure to consumer credit, BNPL, lending or e-commerce risk; Familiarity with git (or another version control system), CI/CD and how pipelines and code get released to production; dbt, or other analytics engineering and data modelling experience; Experience with experiments, control groups or A/B testing.

Условия:

• Attractive packages based on skills and experience.
• The salary band for this position is 32.000 - 44.000.
• Your analysis turns into decisions, and you see the results.
• Exposure to the full credit lifecycle, from approval to portfolio performance.
• A technical environment: you work close to the decision engine and the data pipelines, not only on their outputs.