ING Hubs Romania is seeking a Data Scientist - Financial Crime to join ING Analytics (INGA). You will be responsible for scoping, developing, validating, and documenting machine-learning-based solutions that form the core of our products. You will collaborate closely with other scientists and analysts to ensure the best possible outcomes for our mission.

What You'll Do

Develop machine learning solutions, adopting best practices and quality standards for fit-for-purpose model pipelines.
Challenge the status quo while addressing the requirements of the ING model governance.
Prepare fraud advance models to be deployed to production.
Actively explore INGA’s domain and engage in creating a journey that makes our bank and our society safer.

What We're Looking For

Bachelor's degree in computer science, mathematics, engineering, or econometrics.
1-3 years of work experience in the data science field.
Good understanding of supervised and unsupervised machine learning methods.
Strong Python programming skills, Apache Spark, SQL, Git.
Excellent communication skills, capable of working collaboratively in a semi-remote, globally distributed team.

Nice to Have

Broad experience with end-to-end machine learning projects; involvement in all modeling steps (from data extraction to production).
Background in writing production-ready code and a solid understanding of object-oriented programming.
Proactive and can-do attitude (self-steering).
Curious mindset; you are collaborative and passionate about helping others to grow and improve.
Able to embrace challenges in a fast-changing and complex environment.

Technical Stack

Python
Apache Spark
SQL
Git

Team & Environment

You will be part of the model development & implementation team within ING Analytics (INGA). You will collaborate closely with other scientists and analysts.

Work Mode

This is a local-city role based in Bucharest. We enjoy a flexible way of working and a highly collaborative environment, where fair and constructive feedback is encouraged. Impact is the driver of our work, guided by a shared desire to make the world a better place.