Data Scientist – Banking Analytics & ML, Flexible Work

ING Italia; Milano; In loco; EUR 33.300 - 40.700; Tempo pieno

Vantaggi offerti da questo lavoro

Flexible Smart Working

Meal vouchers & restaurant benefits

Health & Accident insurance

Pension fund & welfare plan

Training & development opportunities

Birthday day off (#doyourbirthday)

Descrizione del lavoro

ING Italia is seeking a Data Scientist to extract insights from large datasets, build predictive models, and implement data-driven solutions across the organization. You will partner with risk, retail, and corporate banking teams to transform data into strategic advantage.

You will collaborate with cross-functional teams, deploy models to production, and communicate findings effectively. A strong background in Python/PySpark, SQL, and ML libraries is required.

Competenze

• 2+ years of professional experience in data science, analytics, or a related field.
• Strong proficiency in Python/PySpark and experience with relational databases using an SQL-like language (preferably SAS).
• Strong proficiency with machine learning libraries and frameworks (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.

Mansioni

• Extract insights from large datasets and develop predictive models.
• Create data-driven solutions to support stakeholder decisions.
• Collaborate with cross-functional and cross-country teams to design experiments and communicate findings.
• Support deployment of models into production ensuring smooth implementation.

Conoscenze

Python

PySpark

SQL

ML libraries

Data handling

Communication

Portfolio (GitHub/Azure)

Formazione

BSc or MSc in Data Science/CS/Statistics/Math

Strumenti

SAS

Git

AWS

GCP

Azure

Descrizione del lavoro

ING Italia is seeking a Data Scientist to extract insights from large datasets, build predictive models, and implement data-driven solutions across the organization. You will partner with risk, retail, and corporate banking teams to transform data into strategic advantage.

You will collaborate with cross-functional teams, deploy models to production, and communicate findings effectively. A strong background in Python/PySpark, SQL, and ML libraries is required.