Data Scientist/AI Engineer

AME (Amsterdam - Maple), Netherlands

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We are looking for a Data Scientist/AI Engineer

Your role and work environment

You work within the Wholesale Banking Global Tribe Lending. The purpose of our Tribe: Make complex lending simple! For borrowers, ING employees, investors and regulators. The Tribe is responsible for easy, reliable, and controlled processes for getting a loan and managing your loan. Also, the distribution of the loans to lenders and investors (amongst other syndications) is part of the scope. Our clients are spread across 40 countries; we are converging to one way of serving our clients, delivering a uniform client experience across countries. As a data scientist/AI Engineer you will work with various squads in the tribe on the automation of loan origination processes, portfolio monitoring, risk monitoring and risk modeling.

Data Scientist/AI Engineer

You will work on advanced analytics, Generative AI (GenAI) initiatives, and/or machine learning use cases. You will leverage your expertise in AI/ML and cloud technologies to create impactful solutions, collaborate across teams, and contribute to innovations in our tech-driven environment. You have broad interests: you enjoy using any data science tools to create value out of data. You’re pro-active in keeping yourself up to date and are always searching for new technologies in the field of Natural Language Processing & Machine Learning for finance. You combine both thinking of the future and a hands-on, right-now attitude. You enjoy working with internal and external customers to refine requirements of your solutions.

The team

The Data Science & Machine Learning chapter is part of the global ING Tribe Lending based in Amsterdam, Dublin & Manilla that has the mission to simplify our lending processes by applying the latest advances in AI. We are part of the technology organization. We work in a fun and creative environment, and we’re dedicated to bringing out the best in both our relations and our projects. You will work in a team of highly skilled professionals and enjoy a creative atmosphere that encourages experimentation and innovation.

Requirements

  • MSc or PhD with a strong focus on math & software engineering (e.g., Computer Science, Software engineering, Data Science, Artificial Intelligence, Physics).
  • Strong programming skills in Python. Java is a plus.
  • Expertise in machine learning, NLP, and/or building LLM-based solutions.
  • Hands-on experience with Python libraries like TensorFlow, PyTorch, Hugging Face Transformers, Scikit-learn, NumPy, Pandas, and Matplotlib/Seaborn.
  • Understanding of  CI/CD pipelines, model monitoring, and observability tools.
  • Understanding of Software Lifecycle Development: Version Control, Build and Deployment pipelines, Containerization.
  • You are a self-starter and have no problem picking up a new skill – be it a framework or programming language.
  • Experience in writing tests and following code quality standards and best practices (unit testing, E2E testing, pep8, flake8 pytest, etc.)
  • Knowledge of working with and creating REST APIs
  • Sharing your knowledge is as important to you as gaining new knowledge – creating documentations and guides to share with your colleagues and organize workshops to share and learn.
  • Experience in working in an agile/scrum way.
  • You are actively contributing to meetings and share your advice and knowledge with technical and non-technical colleagues.
  • You have excellent oral and written English communication skills at technical and business level.
  • You are a team player but can deliver individually in close cooperation with other ING colleagues.
  • You think outside of the box.
  • You see the bigger picture and can connect the dots to help adjust the delivery of the product and focus on the most important features.

Preferred Skills (Nice-to-Have)

  • Experience building or fine-tuning LLMs, implementing retrieval-augmented generation, and working with vector databases.
  • Experience with any major cloud platform (GCP, AWS, Azure).
  • Strong understanding of AI/ML ethics and responsible AI principle.
  • Understanding of SQL and relational databases
  • Understanding of automating ML pipelines and deployment of models using Docker, Azure and Kubernetes.
  • Understanding of Model Lifecycle Management: Continuous Training, Continuous Monitoring (MLFlow, AirFlow, KubeFlow, etc.)

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Agile Airflow APIs AWS Azure Banking CI/CD Computer Science Docker Engineering Finance GCP Generative AI Java Kubeflow Kubernetes LLMs Machine Learning Mathematics Matplotlib MLFlow NLP NumPy Pandas PhD Physics Pipelines Python PyTorch RAG RDBMS Responsible AI Scikit-learn Scrum Seaborn SQL TensorFlow Testing Transformers

Perks/benefits: Career development

Region: Europe
Country: Netherlands

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