Data Scientist
Pubblicato il 13-08-2026 - ING ITALIA in Milano
Our team leverages advanced analytics, from machine learning and quantitative algorithms to data mining and dynamic visualizations, to uncover actionable insights and tackle the most complex challenges across the organization. We own the entire model lifecycle, from exploratory analysis to final implementation. Partnering with stakeholders across all bank’s departments, including risk, retail, and corporate banking, we transform data into strategic advantage.
Responsibilities:
As a Data Scientist, you will be responsible for extracting insights from large datasets, developing predictive models, and creating data-driven solutions to support stakeholders’ decisions and foster a more data-driven organization. You will collaborate with cross-functional and cross-country teams to identify opportunities, design experiments, and communicate findings effectively. Additionally, you will support the team in deploying your models into production, ensuring a seamless and effective implementation.
Requirements:
- 2+ years of professional experience in data science, analytics, or a related field
- Strong proficiency in Python/PySpark and experience working with relational databases using an SQL like language (preferably SAS)
- Strong proficiency with machine learning libraries and frameworks (e.g. scikit-learn, pandas, numpy, matplotlib)
- Strong data handling and feature engineering skills
- Strong communication skills to present insights to both technical and non-technical stakeholders
- Bachelor's or master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field
Preferred Expertise:
- Active portfolio of data science projects on GitHub, Azure, or similar platforms
- Experience with Object-Oriented Programming principles and Git workflows
- Experience with cloud platforms like AWS, GCP or Azure
- Experience in the financial services or banking sector
- Demonstrated solid data handling skills
- Fluent written and spoken English
- Strong verbal an