We are the 100% digital bank of the Santander Group and we are currently undergoing a technological transformation and international expansion. In 2016 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 and we are almost landing 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, we haven´t noticed the change!
Mission and responsibilities:
- This role provides the link between the pure commercial business needs with the analytical engines, creating the link between business areas and a team of data scientists. In particular, Openbank’s Data Science-Risk department ha clear need of data-based solutions that goes from credit scoring to fraud detection. This role will support on the advance analysis of data in order to obtain risk-related insights that foster the development of the data-driven risk strategy of Openbank.
- This position stands within the Data Science-Risks team, and we expect someone that knows how to optimize more than ROC-AUC curves; you have proven experience applying ML engines to improve Business areas outcomes (measured as a trade-off between financial risks and gains) and take data-driven decisions. In the past you have faced data-atheists and does not frustrate you to lead them in the path of data conversion.
- You go far beyond Scikit-learn, TensorFlow, or Keras. You think out of the box, create novel solutions and tailor well-known methods to the required operational constraints as well as disambiguate problems and develop new metrics for identifying and tracking success. You love rigorous analysis, and you are a problem solver that needs to deeply understand the problem to solve, but also understands that an acceptable solution is usually preferred than a perfect solution. You like to continuously think and propose new points of improvement for models.
- You want to find the position where you can participate in the design long-term plans for data-products and strategy, although you understand business urgent requests and sometimes you just need to get the work done. You have worked on several projects at the same time and understand how to balance delivery and progress.
- You enjoy never-faced challenges and data sources, and know how to prioritize opportunities with business needs and Directors’ requests; however our Senior Data Team is composed of ex-members of the most prestigious data-companies and academic programs, and we know that success comes only through collaboration.
- You critical scientific thinking is normally reinforced by listening to others’ opinions with respect to the best algorithmic decisions; however you easily recognize where a logistic-regression will do the job to achieve an 80% acceptable solution.
- Scalable solutions and production-readiness are two of your mantras; however, we have a ML-Operations team that will support you in achieving technical excellence.
- You are not afraid of designing an ETL for a newly introduced dataset, generating concrete specifications for its automation; despite we have a robust Data Engineering team maintaining hundreds of Scala ETLs, the seniority of this role requires being able to communicate with this highly technical team.
- Supervising other fellow data scientists is an attractive point as it can eventually help you achieve bigger more interesting initiatives. In our team, we nurture a meritocratic culture trying to provide professional development opportunities.