Position: Data Scientist
Category: Data Science
English level: fluent
Years of experience: 2


Led and drafted the Recommendation System project. Improved the accuracy of recommendations by 26%. Increased the speed of generating recommendations by 12+ times using concurrence programming. All models were put into production by linking them to the backend using Azure ServiceBus, Redis, Docker.  
	Modelled user behaviour and developed an algorithm to guide users through the patterns found.
	Developed a project for fraud detection with high evaluation score.  After significant tweaking of adaptive recommendations taking the company beyond the break-even point increased profits with the product team by 55%.

	Developed and managed a project to collect, process and standardize hourly weather data for crops. A total of 50 years of hourly data for most countries of the world from various sources was collected and standardized into a single format. Developed the parsing and aggregation of satellite data for the vegetation index.
	Participated in clustering of crops based on satellite imagery. Weather zones were clustered based on weather data, soil composition, vegetative index, etc. Modelled yields for each of the weather zones.
	All projects were automated using AWS services, with EC2 performing the calculations, S3 storing the raw data, and the processed and aggregated data in a SQL.