— Work closely with the Product Management team and Platform engineers to anticipate company needs and quickly put state-of-the-art mathematical tools into the hands of end-user
— Translate real-world problems into the quantitative language
— Find or create algorithms to solve those problems, and implement them in code
— Strive to maintain rigorous scientific and engineering standards
— Work on the full data science pipeline, bringing solutions from basic research all the way to production
— MS or higher in the following areas: Statistics and Mathematics
— At least 3-5 years of professional industry experience, in addition to your academic experience
— Outstanding quantitative analytical ability
— Able to take less than precise business requirements and translate them into logic problems that you enjoy solving
— Independent and creative approach to problem-solving
— Excellent written and verbal communication skills, with prior experience explaining assumptions, conclusions, and methodology to both internal and external customers
— In-depth knowledge of Statistics/Probability/Machine Learning
— General Statistical concepts such as hypothesis testing, estimation, inference
— Supervised and unsupervised statistical techniques such as regression (linear / logistic), time series analysis, clustering
— Machine Learning foundations such as bias/variance trade-off, regularization, dimension reduction
— Real world experience with popular machine Learning algorithms such as Random Forest, Boosting, SVMs
— Strong programming experience in Python and one of the following: Scala/Java, R
— Understanding of algorithm complexity and performance implications
— Knowledge of data structures and algorithms
— Good knowledge of Knowledge Engineering
— Good knowledge of Graph technology, Knowledge Graphs, Graph Databases and Ontologies
— Experience with SQL
— Experience with unstructured text data using NLP methods such as Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), Sentiment Models, Word Embeddings, Text Similarity, Entity extraction is a strong plus
— Familiarity with R Shiny framework is a plus
— You’ll work in a supportive and spirited team of professionals.
— Corporate events, holidays and team buildings for your joy.
— Training and development: we have a huge library (about 500 books!) and a budget for your professional development.
— People-oriented management without bureaucracy.
— Paid vacation and sick leaves.
— Relocation program: if you are from another city and want to move to Kyiv, we will be happy to help you!