With exponential growth in data and new data analytics methodologies becoming available, we are looking for a Data scientist to join Danmarks Nationalbank’s Data Science and Analytics team. You will be part of a dynamic team collaborating with analysts across the bank to generate data-driven insights relevant for policy and supervisory processes. You will exploit modern technologies in analysing and visualising large-scale datasets and apply your skills to find innovative solutions to data challenges relevant to policy supervisory processes.
An exciting and dynamic work environment where you will participate in various projects using a variety of datasets, giving you the opportunity to directly influence policy. The job will be characterized by high engagement, teamwork and clear goals coupled with frequent opportunities to present results internally as well as externally. We have an attractive and flexible work environment where we help each other develop, and you will have continuing opportunity to grow and build your skillset as a data scientist.
As the ideal candidate, you are a curious, driven, and result-oriented individual. You may be newly graduated or with a couple of years’ experience, having practical experience working with real-life, large-scale datasets (e.g. administrative register data). You have a quantitative educational background (MSc in economics, statistics, computer science, engineering, mathematics, physics or similar) that allows you to understand the core mechanisms of data analytics methods and interpret results. Furthermore, you are a strong communicator that both verbally and in written form can synthesize complex analyses and translate them into actionable recommendations. We expect you to also have hands-on experience working with Python or R and associated packages.
Demonstrated skill or experience in (some) of the following areas is also considered an advantage
· Domain knowledge of the financial industry
· Application of machine learning algorithms (supervised or unsupervised learning)
· Data visualisation
· Web scraping or gathering of data via public APIs (e.g. Twitter)
· Unstructured data sources (text, images)
· Understanding of causal inference and associated techniques
· Familiarity working with register data
Do you want to know more?
If you have questions about the position, you are welcome to contact Head of Data Analytics and Science, Thais Lærkholm Jensen, tel. +45 2243 6644.For information considering employment conditions, you are welcome to contact Dorte Kvisgaard, tel. +45 3363 6511.
Apply with relevant exam papers no later than 4th August 2019.