Data Scientist GenAI (LLMs)

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BBVA es una compañía global con más de 160 años de historia que opera en más de 25 países donde damos servicio a más de 80 millones de clientes. Somos más de 121.000 profesionales trabajando en equipos multidisciplinares con perfiles tan diversos como financieros, expertos legales, científicos de datos, desarrolladores, ingenieros y diseñadores.

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At BBVA AI Factory…

BBVA AI Factory operates as a global hub within the Data area of BBVA, with development centers in Spain, Mexico, and Turkey.

Our mission is to build complete, end-to-end data products that solve BBVA's business needs by working closely with business units to transform strategic priorities into actionable, data-driven solutions. Some of our recent projects include:

• Mercury Library, an in-house AI framework now available to the entire data community, aimed at boosting collaboration and accelerating AI solution development. [https://www.bbvaaifactory.com/category/mercury/]
• A machine learning pipeline designed to enhance early debt recovery by predicting default risk and optimizing collection strategies [https://www.bbvaaifactory.com/a-machine-learning-pipeline-for-early-debt-recovery-executive-summary/]
• Applying daily life embeddings to drive deeper personalization in customer interactions and improve service recommendations. [https://www.bbvaaifactory.com/behind-daily-life-embeddings-in-action/]
• Utilizing conformal prediction to provide reliable uncertainty estimates and enhance the confidence in AI model predictions [https://www.bbvaaifactory.com/conformal-prediction-an-introduction-to-measuring-uncertainty/]
• Building algorithmic explainability frameworks to ensure transparency and foster trust in our AI systems. [https://www.bbvaaifactory.com/algorithmic-explainability-how-do-we-apply-it-in-bbva-ai-factory/ ]
  
  

At BBVA AI Factory, innovation isn’t just a goal-it’s a continuous journey.

Sobre el puesto

At BBVA AI Factory we're seeking a Data Scientist to join our dynamic team in Madrid specialized in Machine Learning and Generative AI. As part of the AIF team you’ll collaborate with a diverse group of experts to deliver best-in-class solutions for the agentic ecosystem with focus on evaluation, reusability and business impact. You’ll leverage your technical expertise to propose, ideate and develop production-ready components that bring the state of the art in AI to BBVA.

Key job responsibilities

• Technical leadership: design and deliver reusable components in the agentic and evals spaces, as the lead of a small multidisciplinary team (data scientists and engineers).
• Insight Communication: Present findings and recommendations to stakeholders across the organization.
• Cross-Functional Collaboration: Work closely with product managers, engineers, and designers to implement data-driven solutions and integrate LLM capabilities effectively.
• Mentorship: Guide and mentor less experienced team members to foster growth and success.
• Best Practices Compliance: Ensure all deliverables meet Advanced Analytics governance standards and best practices.
  
  

Your Qualifications

• Education: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related technical field.
• Experience: 2+ years of experience working as a data scientist in the LLM and agentic spaces, including working in multidisciplinary teams.
• LLM Expertise: advanced technical knowledge of LLMs, including model optimization, agent design, evaluation and embedding elicitation.
• AI Evaluation: methodological approach to the evaluation of performance and behavioural metrics, biases and risks of AI solutions, including hands-on experience with evaluation frameworks (like promptfoo, OpenAI Evals, etc).
• Communication Skills: Excellent ability to translate complex technical concepts into actionable business insights.
• Programming & ML Frameworks: expertise in Python, statistical modeling, and machine learning, with proficiency in the traditional data stack (spark, sklearn etc) and the agentic stack (langgraph, agents sdk, etc).
• Applied Machine Learning: Deep knowledge of a broad set of machine learning techniques applied to solve complex business problems, including A/B testing for model performance.
• Ethical AI and Responsible Data Science: Knowledge of ethical AI principles, data privacy laws (like GDPR, CCPA), and a commitment to responsible data science practices.
  
  

Nice to Have

• Previous experience in the financial industry.
• PhD in Computer Science, Statistics, Mathematics, or a related field.
• Team Lead: experience leading a technical team with focus on delivery and business impact.
• Cloud Computing: Experience in AWS, Google Cloud, or Azure for scalable data science solutions, including experience with Docker and Kubernetes.
• Open Source models: Experience developing solutions that leverage open source models (huggingface, etc).
• Experience in Causality: Knowledge and application of causal inference methods to identify and model cause-and-effect relationships.
  
  

Habilidades:

Empatía, Ética, Innovación, Orientación al cliente, Pensamiento productivo