— 5+ years of experience as a data scientist focused on working with financial data and risk modeling
— Good understanding of the machine learning algorithms and their real-world advantages/drawbacks.
— Experience in deploying models to the production
— Good knowledge of SQL
— Advanced knowledge of Python’s data manipulation libraries (pandas, numpy, scipy etc.)
— Experience with deep learning frameworks (tensorflow, pytorch)
— Experience with time-series
— At least Upper Intermediate level of English
— Planning and scoping efforts to deliver on the Machine learning-driven product requirements
— Selecting and building features to be used in the models
— Mining the data from the main database
— Augmenting available data with the data from other sources
— Building software collaboration with the engineering team to exchange the data
— Identifying and building appropriate models
— After February, managing the team of data scientist and machine learning engineers
— Managing collaboration with the Product and Engineering teams
Our patner is ambuilding a cutting-edge accounts receivable management software that uses automation and machine learning to help finance teams become revenue heroes.They’re a rapidly growing company at the forefront of back-office automation, AI, and machine learning and also one of the leaders of the industry in terms of user experience and consumerization of enterprise software.