— At least 2 years of commercial experience in DS;
— Strong knowledge of linear algebra, calculus, statistics and probability theory;
— Knowledge and experience with algorithms and data structures;
— Experience with Machine Learning libraries (NumPy, SciPy, Pandas, ScikitLearn ,etc);
— Experience with at least one of Deep Learning frameworks (Tensorflow, Keras, PyTorch, etc);
— Experience with SQL;
— Strong knowledge of OOP;
— Intermediate English.
— Participation in Kaggle competitions;
— Knowledge of modern Neural Networks architectures (DNN, CNN, LSTM, etc);
— Experience in classical Computer Vision algorithms;
— Experience in Natural Language Processing;
— Experience with production ML/DL frameworks (OpenVino, TensorRT, etc.);
— Docker practical experience;
— Basic understanding of Big Data concepts;
— Experience with Cloud Computing Platforms (AWS, GCloud, Azure).
— Exchange of experience, professional development;
— A strong team, a healthy atmosphere;
— Flexible working time;
— 20 days paid vacation;
— Paid sick leave;
— English lessons and massage service in the office (partially paid by the company);
— Opportunity to take part in conferences, meetups etc. (fully or partially paid by the company);
— Regular company events.
— Data Analysis and Preparation;
— Development of Deep Learning / Machine Learning / Computer Vision solutions;
— You will be working on full-cycle data science projects. Your tasks will include data preparation, developing ML models and deploying them to production. Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains.
We are opening a position for a Data Science Engineer to expand our team.