Generative AI - Intern (Personalisation & CI)

ING Analytics

ING’s goal is to enable people to “make the difference” and empower them to stay a step ahead in life and in business. We are one of the largest banks in Europe and we continuously evolve to become one of the most innovative companies in the banking sector.

The ING Analytics group is a major driving force in ING’s transformation, aimed at helping us to become a data-driven digital leader and creating tangible value for ING and its customers through world-class analytics models, products, and services.

Retail Banking Analytics Data Science Chapter

The Retail Banking Analytics Data Science Chapter provides ING with machine learning expertise for the development of the lending, pricing and personalization analytics. We are based in Amsterdam and consist of 10+ highly-skilled and talented Data Scientists from diverse nationalities and backgrounds (such as physics, statistics, maths, computer science, econometrics, astrophysics). We work in a fun and creative environment, and we are dedicated to bringing out the best in both each other and our projects through collaboration and knowledge sharing. The portfolio of projects is broad and uses a wide range of algorithms and tools, but all relate to risk and pricing. In short, we offer a world-class working environment for data scientists to make an impact and never stop learning.

What you’ll do

As a Data Scientist, you will be

· developing machine learning and advanced analytics solutions for a specific business use case,

· working together with other data scientists,

· actively engaging with stakeholders,

· collaborating with subject matter experts and machine learning engineers to bring your advanced models to production.

Who are you?

· You are highly motivated when solving complex problems and have an always-learning attitude. You keep on top of the latest developments in machine learning and apply them in your projects where they bring value.

· You enjoy sharing knowledge with your teammates and helping others improve alongside you.

· You have a solid and broad background in machine learning, especially in classification and regression. You have experience with algorithms such as random forests, gradient-boosted decision trees, logistic regression, and neural networks.

· You enjoy coding. You have strong Python and software engineering skills, and you know your way around the linux shell. You also know how to use git for version control and SQL dialects for interacting with databases.

· You’re willing to learn: you are self-reflective and open to constructive criticism on both the technical and interpersonal level.

Required skills

· At least 5 years of work experience in the data science field, ideally in the private sector. Knowledge of lending, credit risk, and credit decision domains is a strong plus.

· Broad experience with end-to-end machine learning project implementation. Involvement in all modelling steps from data extraction to modelling and deployment.

· Previously led multiple data science projects

· Strong Python and Spark programming skills. Hands on experience and proficiency in MS Azure Devops and GCP is a strong plus.

· Having a very solid educational background that includes mathematics and statistics (M.Sc. or Ph.D.).

· Strong theoretical knowledge of statistical modelling and machine learning, and a demonstrated ability to apply these to solve business problems and develop innovative models and/or data-driven products.

· Excellent written and oral communication skills in both technical and business contexts.

· Fluency in spoken and written English.