We’re looking for a Risk Credit Data Scientist in Consumer Credit. You will contribute with your knowledge and experience to dig into data analysis and provide solutions for acceptance in consumer credit operations.
You will be responsible for proposing and implementing the best criteria and score decisions optimizing acceptance rate balancing with risk goals. You will be in permanent cooperation with the business units and the more techie part of the Data Department. That’s why a very important part of your role will be to liaise with the business units to identify their needs and provide support to take decisions out of your analysis.
In our growing (+40 people) risk, tech & product team, we have a pragmatic, agile, quality-oriented development methodology: short sprints with continuous delivery, pair programming, TDD with code & design reviews.
We like lean & agile methodologies, XP, good practices, design principles, and patterns.
We enjoy working in a healthy culture that pursues a good balance between personal and professional life and encourages us to keep growing.
Your main missions will be:
- Creating risk models to obtain indicators and trends of the company's credit health
- Ensure quality data for credit risk analysis
- Prepare specific credit risk database in cooperation with data analyst
- Work closely with Platform & Data Engineers in order to define tools needed for extracting and exploiting the information generated
- Define tools with data engineers to be used to extract and exploit information
- Obtain external information to better mix it with internal data
- Analyse data risk information to prepare credit scores for different universes.
- Propose acceptance criteria for merchants and consumers
- Optimize rate of acceptance by analyzing information
- Organize and implement learning information systems that consider the best experience from operational analysts
- Calculate regularly expected losses for current operations
- Participate in the definition of credit risk KPIs
- Help to define short term risk alarms
- Help identify fraud and develop fraud alerts
- Cooperate and impulse methods for risk mitigation
- Help operational analyst proposing proper tools and criteria to optimize individual risk decisions
- Impulse innovation to be in the best practice in risk models
- Consider the proper balance between cost of risk, profitability, and commercial goals to optimize growth-profit tandem
- By in-depth understanding of the merchant selling processes, you will propose and adapt our Acceptance Decision Flows optimizing user and merchant experience as a key strategic advantage. You will cooperate with all risk areas and other departments in doing so.
- Present and explain in a visual way the information obtained to help improving risk decisions
- Communicate solutions and present them to both business and technical stakeholders.
- Not only provide data but extract insights and actionable recommendations with the purpose of helping the business units to make the best decisions.
- Have a comprehensive vision of the business.
- Contribute by proposing the creation of dashboards or other sources of information
- Provide end-user support to data engineers, other analysts, and businesspeople.
What we offer
- Competitive salary.
- Flexible compensation plan (transport, restaurants, ...).
- Real flexible working hours and remote when needed.
- A high degree of autonomy.
- Transparency and open culture.
- Contribute to technical and architectural decisions.
- A tangible impact on the product and also on the company culture.
- Continuous learning:
- Personal budget for conferences, courses, books ...
- 10% of the time to work on any project you're interested in.
- Weekly sessions.
- Free Spanish or English classes.
- Free drinks and fruits.
- All the equipment you need to work comfortably. Our standard set-up consists of a stand-up desk, comfy chair, MacBook Pro, and a 27" external display.
- 23 days of vacation per year + 2 free days.
- Beautiful office based on a bike-friendly location in the center of Barcelona with a big terrace and plenty of nice places nearby.
- Oh! We don't have a ping-pong table here, but we do encourage you to have a healthy work/life balance so you can play in your free time.
- European Work Permit
- Demonstrable experience (3+ years) working as a Credit Risk Data Scientist in a Consumer credit institution in the EU
- A degree in Computer Science, Mathematics, or an equivalent quantitative field
- Excellent command Statistical analysis, modeling, clustering, and data mining techniques to identify trends and insights
- Solid proficiency in Python and experience working with analysis tools such as Pandas, SciPy, Scikit, Pandas, Numpy, Matplotlib, Seaborn
- Jupyter/iPython notebooks, R.
- Ability to write clean, production-ready code.
- Experience with GIT
- Strong experience with SQL queries
- Highly quality and detail-oriented and with a keen eye for accuracy. We need to trust the outcome delivered by the team.
- Write efficient, well-tested code with a keen eye on scalability and maintainability
- A business-oriented attitude will be considered so as you will contribute with a comprehensive vision integrating both, risk and commercial needs.
- Extensive experience with Microsoft Excel-related to data analysis and manipulation.
- Well-developed time management skills. You will have to manage a high volume of requests and we expect you to properly prioritise and set proper delivery expectations (and deliver on time!)
- Ability to do a functional analysis of projects/requests and go down to the technical detail of them (e.g., be able to do good functional analysis, KPI's, dimensions, and identify necessary data sources).
- Excellent interpersonal skills including written and verbal communication.
- And obviously Proactive, Team player, Good 1-2-1- Communicator and Critical thinking.
- Capable to explain Machine Learning projects to business/non-technical people.
- Self-motivation, proactivity, a high degree of autonomy.
Nice to have
- Fluent in spoken and written Spanish.
- Experience in the following technologies:
- Data discovery tools like Tableau, QlikView/Sense, Power BI, or Looker
- Redshift, PostgreSQL (RDS).
- It’s a plus R, Java, or C/C++, and also experience with big data such as Hadoop, Spark, Pyspark.
- Cloud Platform (AWS, Google, …).
What we do is give shoppers tools with which they buy freely, without long processes, in more fair and transparent conditions, and without small print. The future of payment in ecommerce is in what is fair and transparent, in what is common sense.