Data Scientist - Financial Crime @ING Hubs Romania

at ING
EUR 15,000-25,000 per year
JUNIOR MIDDLE
✅ On-site
✅ Visa Sponsorship

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Software Development @ 3 Python @ 6 SQL @ 6 Spark @ 6 Machine Learning @ 3 Data Science @ 5 Communication @ 3 Git @ 6 Mathematics @ 3 Fraud @ 3 Audit @ 3 Compliance @ 3

Details

Company Overview

ING Hubs Romania offers 130 services in software development, data management, non-financial risk & compliance, audit, and retail operations to 24 ING units worldwide. The company has over 2000 high-performing engineers, risk, and operations professionals across two locations: Bucharest and Cluj-Napoca. Their technological core comprises more than 1800 colleagues active in Data Management, Touchpoint Channels & Integration, Core Banking, and Global Products. They encourage a flexible and collaborative working environment driven by impactful work.

Mission

ING Analytics (INGA) drives the digital transformation of ING by creating measurable value through world-class analytics products and services. INGA delivers advanced analytics such as call & speech analytics, generative AI in risk summarization, portfolio performance insights, ESG data insights, and data analytics platforms.

Responsibilities

  • Scope, develop, validate, and document machine-learning-based solutions forming the core of INGA’s products.
  • Collaborate closely with other scientists and analysts to evaluate model performance.
  • Develop machine learning solutions following best practices and quality standards.
  • Prepare fraud advance models for deployment to production.
  • Continuously explore the INGA domain to enhance the bank’s and society's safety.

Requirements

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

Nice to Have

  • Broad experience with end-to-end machine learning projects including all modeling steps from data extraction to production.
  • Experience writing production-ready code and strong object-oriented programming understanding.
  • Proactive, self-steering approach.
  • Curious mindset with a passion for collaboration and helping others grow.
  • Ability to handle challenges in a fast-changing and complex environment.