Data Science & Predictive Analytics Specialist

• Collaborate with Data Engineers to design and build scalable, production grade data pipelines using AWS Glue, S3, Athena, and Redshift.
• Support the transition from legacy data warehouse structures to a lakehouse architecture with bronze, silver, and gold layers.
• Contribute to the design of high quality, well documented datasets for analytical use.
• Provide analytical input on ETL and ELT design, data quality, and performance optimisation.

Data Analysis & Insights

• Conduct advanced statistical analysis to identify trends, patterns, and correlations in large datasets.
• Perform exploratory data analysis and hypothesis testing.
• Translate complex analytical findings into actionable business recommendations.
• Prepare reports and presentations for technical and non technical stakeholders.

Machine Learning & Predictive Analytics

• Design, develop, and deploy machine learning models for business use cases.
• Apply supervised, unsupervised, and time series forecasting techniques.
• Build and maintain reproducible model pipelines integrated into production environments.
• Monitor model performance and drive continuous improvements.

Data Visualisation & Communication

• Develop dashboards and self service analytics using Power BI, QlikView, and Python or R visualisation libraries.
• Create executive level reporting and analytical dashboards.
• Present analytical insights to leadership and cross functional teams.

Collaboration & Data Strategy

• Work closely with Data Engineers, Business Analysts, and governance teams to define data and analytics standards.
• Act as a subject matter expert on statistical methods, predictive analytics, and AI integration.
• Contribute to data governance, metadata management, and data quality processes across multi country initiatives.

Automation & CI/CD Integration

• Implement automated workflows for model testing, deployment, and monitoring.
• Integrate data science and machine learning workflows into CI/CD and infrastructure as code pipelines.

• Experience in data science, analytics, or predictive modelling.
• Advanced SQL skills with a strong understanding of data warehousing and query optimisation.
• Strong programming proficiency in Python (Pandas, PySpark, scikit-learn) and or R for statistical analysis and visualisation.
• Experience developing and deploying machine learning models into production environments.
• Solid knowledge of statistical methods and predictive techniques.
• Experience with AWS cloud services such as S3, Glue, Athena, SageMaker, and Redshift.
• Understanding of data lakehouse architectures and hybrid cloud or on premise data environments.
• Proficiency with data visualisation tools such as Power BI and QlikView.

Nice to have

• Experience in financial services or other regulated industries.
• Exposure to CI/CD, Terraform, or similar DevOps tooling.
• Knowledge of EU data regulations or DORA related frameworks.
• Familiarity with QlikView for reporting and analytics.

Honda Bank is evolving its data landscape towards a modern lakehouse architecture and advanced analytics capabilities. We are looking for a Data Science & Predictive Analytics Specialist to turn complex data into reliable insights, scalable models, and production ready analytics that support business decisions across multiple European entities. In this role, you will work at the intersection of data engineering, advanced analytics, and machine learning. You will help design high quality datasets, build predictive models, and translate analytical findings into clear business value in a regulated financial environment. If you are passionate about data science, predictive modelling, and building robust analytical solutions that go beyond dashboards, this is an opportunity to shape the future of data driven decision making at Honda Bank., Honda Bank GmbH, Sucursal en España is one of the three financial entities that Honda operates in Europe. By joining us, you become part of a big company with strong values, international reach, and a deep commitment to employee development. At Honda, we believe in diversity and inclusion. We are proud to be a fair, equal-opportunity employer where people are valued for who they are, and where everyone contributes to our shared success. If you're ready to shape the future of Honda Bank's data ecosystem, we'd love to hear from you.