Position: data scientist
Category: Data Science
English level: fluent
Years of experience: 7

Churn prediction models and client segmentation for telco operators (regressions, decision trees, clusterization)
Update and finetuning of portfolio optimization with SIT library (optomozation, time series)
Courses on coursera:
data science specialization (Johns Hopkins University)
Introduction to Big Data (University of California, San Diego)
Strategic business analytics specialization (in progress, ESSEC business school and Accenture)
If you want to add science to your impressive data, you is on a right way!
I have strong background in data science, marketing and IT that helps me in fields where all of them are needed: business analytics, big data, machine learning, CRM.
Main data science tool for me is R and RStudio, for data exploration and visualization, creating models and interactive applications.
You can see next word prediction application based on NLP (Natural Language Processing) at https://barvinchenko.shinyapps.io/word_prediction_shiny_app/
Other data science tools I used including Oracle Data Miner and IBM Data Modeler.
My experience with databases and using them for data analysis include SQL databeses: Oracle, MS SQL, mySQL/MariaDB, IBM db2, PostgreSQL, MS Access as well as NoSQL (Mongo db).
BI tools range is not limited to professional level of Excel but Tableau, SAP Business Objects, Oracle BI, Jasper ETL, etc.
My knowledge based on about 20 Coursera courses, LinkedIn Learning, dataCamp and tons of books and articles. And such learning newer stops.