.Head of ML OPS - Data Science & BI (Openbank)Madrid, SpainWHAT YOU WILL BE DOINGWe are the 100% digital bank of the Santander Group and we are currently undergoing a technological transformation and international expansion. In 2017 the re-launch of the Bank began and since then we have been in continuous expansion and growth, especially in our technological side. We work in a start-up format, using agile methodologies to take our clients' experience to the next level. In 2019 we launched the bank in the Netherlands, Germany and Portugal, recently following also the launch in Argentina with others to follow.Our culture makes us different; social and diversity clubs are part of our essence and allow us to live our culture every day. We are a flexible and fast adapting team that currently works remotely most of the time using all kinds of communication tools.Mission and Responsibilities:As a Head of ML Ops, your role will bridge the gaps between existing software delivery infrastructures, DevOps engineers, ML development, training platforms, and data scientists to accelerate the time to value for machine learning models. Your main tasks will include:Model registry for production: code version control + data versioning + model versioning.Model deployment, in batch mode and real-time, test automation, usually in the form of unit tests and integration tests.Process automation for AI retraining, model performance monitoring.AutoML tool technical maintenance, in collaboration with ML Engineering.Work with data engineers regarding data pipelines and data versioning.Adopt the best MLOps standards to design and develop scalable end-to-end machine learning pipelines: Training ML Pipeline + Serving ML Pipeline (CI/CD).Help drive optimization, testing, and tooling to improve quality (unit tests).ETL Design for Business purposes.To be successful in the role you must have:Experience with MLOps framework designing and building machine learning pipelines.Familiarity using cloud platforms (e.G., Azure, AWS, or GCP) to serve machine learning models in production.Knowledge of code development best practices and tooling (e.G., version control, test-driven development, CI/CD).ETL and/or data wrangling techniques.Proficiency in Python / PySpark development.Knowledge of containerization technology (Docker/Kubernetes) and REST API design.Business storytelling and communicating data insights in a business consumable format.Agile methodology for teamwork and analytics 'product' creation.Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities.Ideally, statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.What do we offer?Immediate incorporation to a dynamic and agile company with a growth and expansion project.Working in start-up mode with the support of Grupo Santander.Competitive remuneration and attractive benefits package