In this role, you will be working on implementing core infrastructure functions for data sourcing and processing (incl. DQ controls, data adjustments, etc.).
8+ years of overall Data Science / Date Engineering experience within Financial Services or similar highly regulated environment
Coding proficiency in at least one of the following: Python (PySpark), Java/Scala, SQL and/or SAS
Good understanding of applying statistical modelling, machine learning and / or exploratory analysis to large datasets
Experience with relational database programming and distributed data processing at scale using Spark (PySpark)
Feeling safe in assembling data sets from disparate sources and analyze using appropriate quantitative methodologies, computational frameworks and systems
Excellent people management abilities and good communication skills that enable you to collaborate effectively
Fluent in English, German or French would be a plus
Close engagement with other project teams and to collect requirements for needed infrastructure capabilities for implementing fully functional Credit Risk reporting applications and enabling digitalized BAU processes, while complying with regulatory rule set for Risk Reporting
Supporting a dedicated squad team on specifying user stories and managing the backlog for implementation; implementing solutions, as well as performing UAT of provided solutions
Engage with senior Business users in automating regulation and compliance to build a state-of-the art regulatory reporting and analytics infrastructure
Develop and design algorithms, build prototype versions, run multiple validations with business experts and work on building products
Off to new destinations! Apply now directly on email@example.com or contact our team on +41 44 485 44 99.