Researching, designing, and implementing machine learning algorithms;
Communicating results, technical constraints, and decisions to the business and non-specialists;
Delivering rapid prototypes and proof of concepts that demonstrate real value;
Creating and delivering progress reports, slide decks, proposals, and documentation.
Upper-Intermediate English (B2) or higher;
A BS or higher in computer science or a related field;
4+ years of experience in software development;
2+ years of experience in Data Science;
Extensive knowledge of and practical experience in Machine Learning, Recommender Systems, and Algorithms;
Understanding of Machine Learning techniques like Linear Regression, Decision Trees, Collaborative Filtering, Anomaly Detection, etc.;
Practical experience with high-level programming language like Python and DS frameworks;
Proficiency in database query languages such as SQL;
Understanding of the ETL process;
Knowledge of Linear Algebra, Probability and Statistics, and Numerical methods;
Understanding of software development process, Agile approach, and CI/CD.
Experience building large-scale recommender engines (collaborative filtering, KNN, associative rule learning, custom similarity metrics, etc.);
Understanding of predictive analytics (time-series analysis and forecasting, survival and duration analysis, etc.);
Ability to apply graph analysis techniques for structural pattern recognition;
Applied statistics skills, such as distributions, hypothesis testing, regression analysis, etc.;
Experience building microservices and containerized applications (Docker, k8s);
Familiarity with Big Data frameworks — Hadoop, Spark Experience with Natural Language Processing NoSQL databases, such as MongoDB, Cassandra, HBase;
Experience with mining of structured, semi-structured, and unstructured data;
Experience with data visualization tools, such as Ggplot2, Plotly, Matplotlib.
Work on interesting and challenging projects, while building a pioneering software category;
Great atmosphere, with the vibe and energy of a high-growth tech company;
Option of equity;
Close collaboration between UA and US team members;
Ultramodern office in the heart of Lviv (Magnus) and Kyiv (Gulliver);
Flexible working hours;
Complimentary dinners (like Pizza Friday!);
English classes and an immersive English-speaking work environment (we have a lot of native speakers at the office).