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Chapter Lead Data Engineering - Financial Crime & RegTech
  • Python
  • Spark
  • Machine Learning
  • Big Data
  • Hadoop
  • Deep Learning
  • PyTorch
118 days ago

Chapter Lead Data Engineering - Financial Crime & RegTech

Who are we?

ING’s goal is to enable people to “do their thing” 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, which formed two years ago, is a major driving force in ING’s transformation, aimed at helping us to become a data-driven organization, where advanced analytics is at the heart of our business processes.

In our center of expertise, we create advanced analytics applications in the financial crime, regulatory technology (RegTech), and “Know your customer” (KYC) domains. We are tackling fundamental, high impact, problems in the financial services industry. We are passionate about protecting both our customers and our society, delivering products that make ING a safer and more compliant bank. We are building advanced analytics solutions and systems to augment ING capabilities in areas such as anti-money laundering (AML), human trafficking and customer due diligence. Our group consists of roughly two dozen data scientists, software developers and domain experts, working together to deliver innovative solutions in our domain across multiple countries.

What is the role we hiring for?

As we continue our growth and establish the added value analytics brings to our domain, we seek a profile which can help us “level-up” our capabilities to make an impact - in scale, quality and delivery time. We are looking for someone who can lead and develop a team that will:

  • Support our transformation as a group from building statistical models to delivering data products.
  • Allocated roughly 50% as technical contributor for developing an designated advanced analytics product in the financial crime domain.
  • Support our machine learning engineers (both backend and frontend) to grow in their capabilities and craftsmanship and to be successful in their own teams.
  • Help us to align with the ING Analytics group technical architecture and data engineering teams, applying CI/CD standards and solutions to our work as a group.
  • Help us design products which generalize and are configurable for different domains and different countries.
  • Challenge the status-quo & and help us shape a new way of working for the center of expertise.

Who should apply?

At ING, we promote diversity not just because it is the right thing to do, but because it’s essential for delivering on our strategy. In order to stay a step ahead we need teams with a healthy mix of contrasting perspectives and backgrounds as they are more creative, faster to adapt and more inventive with their solutions. We strive to hire a workforce as diverse as the communities in which we operate, and we will consider every application, regardless of race, religion, color, national origin, sex, disability or age.

If you are an experienced (6+ years) software developer or technical team lead with system architecture capabilities and experience in putting testing, continuous integration and continuous delivery (CI/CD) solutions in place for data science products and with a track record of nurturing talent to their full potential, we would love to hear from you.

Additional optional criteria which will be considered separately as a “plus”:

  • An object-oriented mindset with experience in applying design patterns in production setting at scale.
  • Strong python development skills.
  • Experience developing machine learning pipelines or applications utilizing machine learning techniques.
  • Experience with industry-accepted testing tools and frameworks (such as Selenium, TestNG, JUnit, and/or Cucumber, etc).
  • Experience configuring CI/CD solutions (such as Jenkins, Gitlab CI, TFS, Docker, etc).
  • Experience configuration CI/CD solutions for machine learning - CD4ML (such as MLFlow, Pachyderm, Kubeflow, Seldon core, etc).
  • Experience with deep learning frameworks (such as Tensorflow, PyTorch etc).
  • Experience with open source big data frameworks (such as Hadoop/Hive, Spark, etc).
  • Experience writing RESTful web services (preferably in Django / Flask).
  • Experience in front end development or web development frameworks like Polymer, Lit, React, Vue.js.
  • Experience leading a development team.
  • You have a deep knowledge of engineering processes practices in banking and finance,

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