Machine Learning Engineer (m/f/x)

  • ING Deutschland
  • Frankfurt am Main, Germany
  • 14/10/2021
Full time Data Science Data Engineering Machine Learning Data Analytics Big Data Business Intelligence Statistics

Job Description

 

Machine Learning Engineer (m/f/x)

Information Technology | Berufserfahrene | Frankfurt am Main

Apply

Your competencies bridge any gap between Data Science and Software Engineering? International collaboration paired with technological entrepreneurship is exactly your cup of tea? Perfect! Join our International Advanced Analytics Team and get into the mix with constructive passion!

Your Tasks

In your day-to-day operations, you apply ML algorithms, implement and evaluate ML models and transfer them into production. Eagle-eyed, you analyse the requirements of the business departments concerning Business Intelligence, DataWarehouse, Big Data, translate them into smart designs and monitor their operation. You easily identify which features, products, and technologies will bring our processes forward and track down new trends. In projects, you take over the IT part - always in close international exchange with your team and various stakeholders.

Your Profile

  • Master‘s degree in computer science
  • Several years of professional experience in dealing with Machine Learning models incl. production
  • Experience with statistical methods / Machine-Learning-methods such as Random Forest, Gradient Boosting, Time Series Analysis, Regularization, Causality, Bayesian statistics
  • Familiar with Big Data platforms and tools such as Hadoop, Spark, Flink
  • Sound know-how in data science / software development incl. testing, continuous integration, code reviews
  • Very good knowledge of Python and libraries such as scikit-learn, pandas, numpy, tensorflow
  • High intrinsic motivation as well as enjoyment of international collaboration (business trips in Europe, if necessary, of approx. 10%)
  • Fluent in Business English is required and German is an advantage

 

At ING we are colorful and diverse: different personalities with different perspectives - an international culture where we value and appreciate each other. We believe in substance over style, people instead of labels.
Come as you are.