The responsibilities of this person will include development of components using object oriented programming following good coding practices and extensive components testing. Additionally, a person will be involved in the full lifecycle of forecasting application development: from data preparation, through modeling, evaluation, productization to maintenance.

Practical skills required:

• [must have] 3+ years of professional experience, using Python for machine learning solutions development
• [must have] understanding of machine learning techniques and algorithms (supervised learning, hybrid models, train/test data sets, overfitting, model evaluation, etc.)
• [must have] ability to write high quality code in Python
• [must have] professional experience in object oriented programming
• [must have] at least basic understanding of time series analysis concept
• [should have] ability to structure an emerging solution code into well engineered software packages
• [should have] experience with or willingness to learn time series forecasting methodologies
• [should have] experience, knowledge or willingness to learn modern Deep Learning frameworks for forecasting
• [should have] ability to apply unit testing and DevOps / CI/CD / ML engineering techniques
• [nice to have] experience with Docker

The successful candidate should also:

• be team-oriented, proactive, and collaborative
• be an excellent problem solver and analytical thinker
• be a good communicator
• be willing to learn and expand their skill set
• be able to communicate in English at the level of: C1+
• Degree in Data Engineering, Computer Science, Statistics, Mathematics, Information Systems or other relevant experience
• of 4 years of overall professional experience including: – at least 4 years of professional experience in Data Science
• Practical experience in any of the areas: Computer Vision, NLP, Predictive Modelling – Experience should be covered by projects that person delivered
• Technology-related skills: – SQL databases (intermediate level) – Python or R and related libraries (intermediate level)
• Very good understanding of Data Science basics: train/test model data sets, overfitting, classification, clustering, etc.
• Basic experience (ability to use) of technologies supporting building data pipelines: Ansible, Bamboo, Docker, Kubernetes, Git, etc.
• Knowledge of and experience of working using agile methodologies
• Responsible, reliable, goal and problem solution-oriented

B2B contract and full remote work

We reserve the right to contact the selected candidates.