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Data Scientist

Key Facts

Remote From: 
Full time
Spanish

Other Skills

  • Business Acumen
  • Communication
  • Teamwork
  • Persuasive Communication
  • Willingness To Learn

Roles & Responsibilities

  • Degree in a numerate discipline or equivalent professional experience; post-graduate qualification (MSc or PhD) preferred but not essential.
  • Proficiency in Python and SQL for data analysis and modelling.
  • Experience with regression and tree-based methods (e.g., linear/logistic regression, GBM, random forest).
  • Knowledge of GDPR and data governance; familiarity with cloud platforms (Azure/Databricks) and AI/LLMs is desirable.

Requirements:

  • Build strong working relationships with Spanish Strategy, Operations, Pricing and Data Engineering teams; deliver hands-on analytical projects from problem definition through deployment and monitoring.
  • Develop statistical, machine learning and LLM-based models to agreed objectives and timelines; translate analysis into commercially viable, operationally realistic recommendations.
  • Ensure customer outcomes, fairness and experience are central to decision science work; translate complex analyses into actionable recommendations.
  • Coordinate with UK-based Decision Science and Data Engineering teams to support operational implementation and promote sound analytical methodologies and development standards.

Job description

The role is embedded day‑to‑day with the Spanish business, supporting local Strategy, Operations, and Pricing teams, while also collaborating closely with a broader Decision Science team that is predominantly based in the UK. Strong remote working practices and cross‑country collaboration are therefore essential.

The Decision Science team applies statistical modelling, machine learning and emerging AI techniques to:

  • Understand, measure and predict customer behaviour across the credit lifecycle
  • Optimise collections and customer treatment strategies
  • Value portfolios of non‑performing or distressed assets through cash‑flow and cost projections
  • Improve operational efficiency and customer outcomes through data‑driven decisioning

The successful candidate will deliver end‑to‑end analytical solutions that move from data exploration and modelling through to operational deployment and performance monitoring in live business processes.

Key Outcomes of the Role

The successful candidate will:

  • Support the growth of the Spanish business, while benefiting from Group‑level standards, tools and expertise
  • Deliver hands‑on analytical projects from problem definition through to deployment and monitoring
  • Translate complex analysis into actionable, commercially viable recommendations
  • Ensure customer outcomes, fairness and experience are central to decision science work
  • Become a trusted analytical partner to Spanish stakeholders, while contributing to the wider UK‑based Decision Science team

Key Responsibilities

Direct Responsibilities (Delivery)

  • Build strong working relationships with Spanish Strategy, Operations, Pricing and Data Engineering teams
  • Develop statistical, machine learning and (where relevant) LLM‑based models to agreed objectives and timelines
  • Develop deep understanding of Spanish data sources
  • Translate analysis into commercially viable and operationally realistic recommendations
  • Work with business and technical teams to ensure models are effectively deployed into live decision‑making
  • Identify opportunities to enhance modelling approaches and analytical tools used across CCM

Shared Accountabilities (Influence & Collaboration)

  • Promote sound analytical methodologies and development standards across projects
  • Contribute to realistic project planning and prioritisation
  • Support initiatives to improve data quality and analytical capability within the Spanish business
  • Coordinate with UK‑based Decision Science colleagues and Data Engineering to support operational implementation

Personal Attributes

  • A creative, structured problem solver
  • A confident communicator able to explain complex ideas clearly to non‑technical audiences
  • Comfortable working with geographically distributed teams
  • Curious, adaptable and motivated to learn

Education & Certification

  • Degree in a numerate discipline or equivalent professional experience
  • Post‑graduate qualification (MSc or PhD) preferred but not essential
  • Relevant technical certifications (Python, SQL, cloud platforms, AI/LLMs) are desirable

Knowledge & Experience

Essential

  • Python and SQL for data analysis and modelling
  • Regression and tree‑based methods (e.g. linear/logistic regression, GBM, random forest)
  • Advanced Excel skills, including data validation and analytical modelling

Desirable

  • Experience with Azure, Databricks or similar cloud platforms
  • Exposure to LLMs (prompting, evaluation, or applied use cases)
  • Experience working with collections, recoveries or distressed debt data
  • Knowledge of GDPR and data governance

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