Requirements:
— Good knowledge in machine learning i.e. random forest, xgboost, clustering algorithms, dimensionality reduction(PCA, t-SNE). A good foundation in basic statistics and linear algebra
— Strong knowledge of Python
— Time-series analyses
— Anomaly detection
— Comprehensive knowledge of the Python data analysis ecosystem (Pandas, Numpy, Scikit-learn, etc.);
— At least minor experience with python visualization tools(matplotlib/seaborn, Plotly)
— Experience with following neural network architectures: LSTM, GRU and other RNN-based
— Strong practical experience with Deep Learning frameworks like PyTorch, MXNet, Tensorflow, or Keras
— Upper-intermediate level of English mandatory
Would be a plus:
—Experience with R, C++
—Familiarity with time-series predictive/anomaly detection analyses, natural language processing, signal processing
—Understanding SOTA approaches for machine learning problems like unsupervised/semisupervised learning.
—Experience with the following DL frameworks: DLib, Darknet, Theano
—Awareness of the CRISP-DM process model
—Experience with continuous integration and release management tools, preferably within the AWS platform
—Hands-on Experience with the common architecture of MLOps system by the means of Hadoop, Docker, Kubernetes, cloud services and experience with managing production ML lifecycle
With us you can:
Develop your technical knowledge:
— Use latest technologies
— Participate in technical events and conferences (the cost is covered by the company)
— Regular techtalks and professional development
Improve your soft skills:
— Build strong teamwork skills and become an essential part of the dynamic teams
— Improve your English at classes and speaking directly with clients
— Increase your productivity and communication level via Scrum, Kanban, Agile methodologies
What else do we offer?
— Competitive compensation and benefits
— Flexible and negotiable schedule
— Nice and comfortable office located near metro station
— Covered rest period (20 business days)
— Free English classes (we have 3 teachers in our team)
— Break area with Xbox, air hockey, ping-pong and table soccer
— Truly friendly atmosphere and unforgettable events
— Bookcrossing
— Basketball and ping-pong teams
— Discounts offered by individual bonus cards (our partners are coffee shops, bars, and fitness centers)