The way people interact with money in the 21st century sucks. Managing your money should be easy, engaging, playful, effective and convenient.
At zuper, we are working on the first truly personal financial coach in your pocket to make this happen. We are looking for a Machine Learning and Data Scientist with a proven record to help us develop prediction models and anomaly detection.
The ideal candidate has a deep mathematical understanding of machine learning and has applied this to solving challenging problems as illustrated by their innovative Ph.
D. or postgraduate work. This position is suited to a person who has recently completed (or is soon to complete) their Ph.
D. and is excited about applying their skills to advancing the state-of-the-art in the area of predictive analytics. That’s why we need YOU.
IN THIS ROLE YOU WILL HAVE FOLLOWING RESPONSIBILITIES :
Modeling research designs and experimental model architectures for development of signal detection features
Well-crafted, maintainable, and performant machine learning code
Clear, reproducible algorithm specifications
WE ARE LOOKING FOR :
Ph.D. or other post-graduate work in Electrical Engineering, Computer Science, Math or Statistics (recent graduate or Ph.D. under review)
Expert in modeling temporal and sequential data using recurrent neural networks (RNNs, LSTMs)
Recent high impact publication record
Strong communication skills
Expert knowledge of existing deep learning frameworks (e.g., Theano, TensorFlow, Keras)
Scientific and numerical programming in Python
Strong bash / shell scripting
Proficient working with UNIX operating systems
Proficient understanding of code versioning tools, such as Git
A passion for continuous learning and understanding.
BENEFITS & PERKS :
Join the core team and work towards a lead researcher position
Work remotely or in our great offices in Niš or Vilnius