Altro · Milano, Lombardia, Italia · · 64.935€ - 79.365€


Descrizione dell'offerta

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 and written communication skills

Contract offer: Working hours:

Full time (37 hours per week)

Applicable Collective Labour Agreement:

National Collective Labour Agreement for employees in the credit sector (NCLA)

Annual base salary starting from:

Euro 37,000€

Variable remuneration:

in line with the applicable remuneration policies (with a target based on the role, outcomes linked to the Group, Business line/function, and individual performance)

The benefits of joining ING:

Flexible Smart Working

Competitive base salaries and performance-based bonuses

Meal vouchers and corporate restaurant and bar

Health insurance and Accident insurance

Pension fund and welfare plan

Diverse cultures & Innovative mindsets

International Environnent and Talent Program

Commitment to sustainability

Lots of training development opportunities to help you grow

Lots of moments dedicated to physical and mental well-being

A special day off when it is your birthday: we call it #doyourbirthday!

And of course, we can’t forget free water & coffee at the office!

About ING: ING offers many opportunities to build a diverse and rewarding career. You will be joining an international innovative digital bank, the first in Italy to adopt a fully flexible smart working model, and you will be working in a stimulating environment where you can grow both as an individual and as a professional.

Our purpose - empowering people to stay a step ahead in life and in business - represents our belief in people’s potential. We don’t judge, coach or to tell people how to live their lives. We empower people and businesses to realize their own vision for a better future.

Our Commitment: Diversity is a fundamental element of our corporate culture, and we are fully committed to creating a safe and inclusive environment, based on mutual respect and the value of diversity, offering equal job opportunities to all qualified candidates.

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Informazioni aggiuntive

Opportunità: Data Scientist a Milano, Provincia di milano

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Competenze valorizzate

  • Python
  • Azure
  • Machine Learning
  • Pandas
  • NumPy
  • Analisi

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