Python NN/ML engineer, D TRADING in DTEK, TOV, Energetichna kompaniya

Vacancy in LLC D.TRADINGD.TRADING - trade in energy products. This is a client-oriented business, focused on the reliable supply and provision of quality services in the field of energy resources (electricity, natural gas, gas condensate, coal). Position functions: Development and improvement of neural model architecture. Development of descriptions of data loading and processing algorithms, calculation of factors, calculation models costs, forecasting models and accuracy assessment. Development of Python scripts that implement these algorithms. Integration of developed Python scripts with the IT infrastructure of an analytical solution. Testing of scripts on historical and forecast data and assessment of their accuracy. Presentation (visualization) of work results to internal clients .Analysis and forecasting of commercial and physical parameters of the energy market using NN/ML.Analysis of commodity market logistics, construction and implementation of netback calculations.Update of implementation descriptions based on the results of development and testing of developed scripts, including data model, reference book, IT architecture, network interaction diagram , technical project, description of analytical solution algorithms, implementation description. Construction of forecasting models of weather data (working with timeseries). Hypothesis testing of trading ideas and statistical analysis to confirm them. :PyTorch,Spark, Polars,Pandas, Numpy, SciKit-Learn, SQLALchemy, Matpotlib, Tornado, Keras, Tensorflow, psycopg2, Seaborn, plotly, Selenium. Experience in commercial development based on PostgreSQL DBMS. Knowledge of mathematical statistics, including probability distribution , stochastic processes. Knowledge and experience in applying modern methods of data analysis, including panel and graphical data analysis, methods of cleaning, transformation and normalization of data, methods of interpolation and extrapolation. Ability to formulate and test hypotheses using statistical methods. Proficiency in MS Office (Excel, PowerPoint , Word, Outlook). Higher education. The following professional skills will be a plus: Experience with AWS (SageMaker, Redshift, DMS, S3). Experience with PostgreSQL DBMS. Experience with BigData. Knowledge of the theory and practice of machine learning methods (TransformerNN, LSTMNN ,NPLModels).Knowledge of methods for assessing the accuracy of predictive models.Experience in developing and supporting neural networks.Skills and experience in time series analysis, time data processing, data preparation for time series modeling. activity; The possibility of working according to a hybrid schedule - work in the office/remote work; Participation in interesting projects; clubs, professional communities).