Risk Data Scientist | Risk Management @ING Bank

ING Groep N.V.
United States
about 2 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, Romanian
Job source

Tech stack

Microsoft Azure Big Data Data Integrity Python (Programming Language) Machine Learning Microsoft Office Oracle (Applications) Raw Data SAS (Software) SQL Databases Model Validation Data Management

Job description

Within the Risk Data Science team, our mission is to design and continuously improve the credit risk modeling landscape, enabling sound and responsible credit decisions throughout the entire loan lifecycle. In this role, you will contribute to building models that directly support sustainable business growth while maintaining strong risk management practices.

About The Team

You will join a collaborative, forward-thinking team where analytical rigor meets innovation. We work with large datasets, modern tools, and advanced methodologies, including machine learning and AI, to extract meaningful insights and drive impactful decisions.

Our team thrives on open communication, knowledge sharing, and continuous learning. We partner closely with colleagues across Risk, Business, IT, and Model Validation functions to ensure that our models are not only technically robust but also aligned with real business needs.

Your day-to-day, In this role, you will support the full lifecycle of IFRS9 and Credit Decision models for retail, micro-companies, and SMEs. Your responsibilities will include:

  • Developing and calibrating models end-to-end, from scope definition and data collection to estimation and documentation
  • Supporting the implementation of models in internal systems
  • Monitoring model performance, interpreting results, and proactively suggesting improvements
  • Ensuring compliance with internal governance frameworks and methodologies
  • Preparing for independent model validation processes and addressing findings in a timely manner
  • Contribute to defining optimal cut-off strategies for Credit Decision Models, balancing risk and acceptance
  • Perform recurring and ad-hoc portfolio analysis to identify both opportunities and high-risk segments
  • Support business initiatives by selecting and analyzing client data for targeted campaigns
  • Ensure data integrity and proper data management in line with credit risk policies
  • Automate scripts and document workflows to improve efficiency and reliability
  • Apply advanced statistical techniques, including machine learning and AI, on complex datasets
  • Participate in global projects aligned with the bank’s strategic priorities, * Impactful work in a fun and collaborative environment.
  • Open-concept offices designed for both team work and relaxation.
  • Corporate events and social gatherings.
  • Hybrid way of working with flexible working schedule and short week options.
  • Monthly budget on Benefit platform.
  • Extra annual leave days depending on the total length of working experience.
  • Growth opportunities through upskilling/reskilling programs and a variety of learning and development platforms: ING Learning Centre, Udemy, Bookster, trainings and certifications.
  • Possibility to access internal roles, International Short-Term Assignments or Long-Term Assignments.
  • Context to make an impact through Sustainability and Corporate Social Responsibility projects.

Requirements

  • Degree in Mathematics, Statistics, Cybernetics, or a related field
  • Fluent in English (written and spoken)
  • Experience in model development or validation is a plus

Technical Skills

  • SAS, SQL (Microsoft/Oracle), Python
  • Microsoft Office tools
  • Familiarity with Azure DevOps
  • Understanding of lending markets and banking regulations (both Romanian and European)

Personal competencies

  • Ability to see the bigger picture and make well-balanced decisions
  • Strong organizational, planning, and prioritization skills
  • Analytical thinking and problem-solving mindset
  • High attention to detail and accuracy
  • Proactive attitude, energy, and adaptability in complex environments
  • Strong communication and influencing skills
  • Emotional intelligence and collaborative mindset

About the company

Discover ING Bank Romania

ING believes in a world where everyone has the right to grow and progress in their own way. We express this in our global tagline, “do your thing”. Perhaps more than in any other large company, we extend our belief in the power of autonomy to our own people. But there’s a catch. In return for great freedom, we expect people to do great things for our customers, our stakeholders, and ING at large. To work here is to be surrounded by people who are energetic, ambitious, friendly and respectful: talented specialists who take responsibility and autonomy to make great things happen. We stay curious, thrive on change, and seek new and better ways to make it happen. Active in Romania for 30 years, ING Bank pioneered and challenged the local banking industry. Technology and innovation are at the core of what we do, making our products relevant for our customers’ lives and businesses. ING Bank Romania is the only bank with an organic growth within the top 10 local banks by assets, without acquisitions of client portfolios or other banks. ING Bank Romania is an universal bank with more than 1.9 million customers from three business segments: individuals (retail), SME and Mid-Corporate companies and Wholesale Banking.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on arc.dev

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

4:26 min

Speaker introductions and overview of ING bank

Doraly Chezeu Sukem Doraly Chezeu Sukem +1 · WWC 2024

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

4:09 min

Challenges of interpreting raw data with language models

Clemens Vasters Clemens Vasters · WWC 2025

1:14 min

Evolution of distributed SQL database architectures

Wei Hu Wei Hu · WWC 2024

2:39 min

Navigating strict environments for enterprise banking

Lea Fragner · LIVE

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

Videos

See all

Related articles

See all