Building Europe’s most valuable open data money platform.
Our Yolt Platform
Yolt is the leading open banking provider in Europe, building, managing, and maintaining AIS and PIS connections for top financial institutions and ambitious tech businesses. In January 2018, we became the first-ever Third-Party Provider to successfully make an open banking API call. Just over two years later, we have now made more than 1 billion API calls, accounting for 50% of all traffic.
At Yolt, data is at the core of what we do. Within our advanced analytics (aka data team), we have the unique position to use the latest tools and techniques to fuel our passion to create valuable insights on transaction data.
Working in a state of the art, AWS driven platform, you’ll have all the tools available you need. We don’t shy away from a challenge to design and create the models that bring unique and high value enrichments and insights to our customers.
Our team is driven and ambitious with a strong focus on collaboration to go further than any one of us could go alone. The customer is our focus as we build the tools to make them move faster and get more value out of the incredibly rich open banking data. We deliver fast, aim for excellent and high-quality products.
What we are looking for
Are you getting excited about all of the above? Do you get up in the morning with your head full of ideas how to improve or develop new models that bring unprecedented value insights? Or are you the kind of person who wakes us slowly, over a great cup of hand brewed, complex blend coffee, while dreaming about statistical analysis, AI and machine learning? Either way, we are happy to meet you!
As medior/senior Machine Learning Engineer, you play a pivotal role in the development and operation of ML solutions at Yolt.
Together with our team and stakeholders, you refine new use cases or extensions, by mapping product requirements to ML solutions. Moreover, you are keen on leveraging your knowledge and creativity to innovate with more advanced algorithms, such as metric learning label embedding neural networks, built in TensorFlow (check out this PyData talk for a preview: https://www.youtube.com/watch?v=_I_HCr-mfhM).
Building on your experience with software engineering and solution architecture, you take responsibility for experimental code being translated into properly tested CI/CD training-serving pipeline (Gitlab, S3, SageMaker, Airflow). In parallel, you actively liaise with the Data Engineers to make sure models are served in production in a streaming microservice environment (Scala, Kubernetes, Kafka, Cassandra). Because your pipelines and services impact real users, you will not rest assured unless they are properly tested and monitored (Prometheus, Grafana).
Apart from the model development, you’ll be responsible for deep dive, statistical analysis to help in understanding our business and customers better or to compose a use case to be used in conversations with customer to show the value that is hidden in the open banking data.
Within the team, we foster a culture of knowledge sharing and continuous learning, facilitating you to keep abreast of the latest developments in the field. You signal impediments and advise on the adoption of new tools and frameworks. To get inspired and expand your network, you attend meetups and conferences. Here, you also regularly showcase our work that ultimately enables Yolt users to leverage the treasure hidden in the data.
What you'll need
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