Excited to grow your career? BBVA is a general company with more than 160 years of history that operates in more than 25 countries where we serve more than 80 million customers. We are more than 121,000 professionals working in multidisciplinary teams with profiles as diverse as financiers, legal experts, data scientists, developers, engineers and designers.
Learn more about the area: At BBVA AI Factory we operate 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 but are not limited to fraud detection, risk management, and debt recovery. At BBVA AI Factory, innovation isn’t just a goal—it’s a continuous journey.
About the job
We’re seeking an Expert Data Scientist to join our dynamic team in Madrid. The role focuses on building end‑to‑end data products that incorporate cutting‑edge AI to enhance key banking processes. You will collaborate with a diverse group of experts to develop a new AI‑supported customer relationship model that benefits both customers and managers.
Key job responsibilities
- Lead Analytical Projects: Manage and execute key analytical projects within the DATA area, aligning with strategic objectives, while leading teams to ensure successful delivery.
- Data Analysis: Analyze large and complex data sets to uncover trends and insights that drive business decisions.
- Model Building: Develop predictive models using statistical and machine‑learning techniques.
- Cross‑Functional Collaboration: Work closely with product managers, engineers, and designers to implement data‑driven solutions.
- Insight Communication: Present findings and recommendations to stakeholders across the organization.
- 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 field.
- Experience: 5+ years working as a Data Scientist in multidisciplinary projects.
- Databases: Strong SQL skills; experience with relational databases.
- Programming: Strong skills in Python, PySpark, and R.
- ETL Development: Ability to design efficient data extraction, cleaning, and transformation processes.
- 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.
- Communication Skills: Excellent ability to translate complex technical concepts into actionable business insights.
- Ethical AI and Responsible Data Science: Knowledge of ethical AI principles, data privacy laws (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.
- Cloud Computing: Experience with AWS, Google Cloud, or Azure for scalable data science solutions, including Docker and Kubernetes.
- Deep Learning: Hands‑on experience with deep‑learning frameworks such as TensorFlow, PyTorch, or Keras.
Why You’ll Love Working Here
- Play a key role in creating an easier, more personalized banking experience with better service for our customers.
- Work on AI‑driven improvements to fraud detection, risk management, and debt management.
- Help develop a new customer relationship model supported by AI, benefiting both end customers and managers.
- Collaborate with professionals from data science, machine‑learning engineering, solution architecture, development, analysis, and product management.
- Embrace our obsession with innovation, reusable components, and rapid customer‑centric delivery.
Skills
- Algorithms
- Cloudera Data Science Workbench
- Data Science
- ETL Development
- Structured Query Language (SQL)
- Timetabling
