MAJOR SKILLS: DATA SCIENCE, BUSINESS ANALYTICS, DATA MINING

Vladimir has a rich background in data science and software engineering, spanning several years and various industries. His expertise in machine learning, statistics, and analytics equips him with a profound ability to develop and refine data models and mining algorithms. Additionally, Vladimir excels in applying advanced statistical techniques to analyze large datasets, providing insightful and actionable solutions to intricate business challenges. His comprehensive experience underscores a strong capability to translate complex data into meaningful, results-driven strategies. Skills Programming Languages: Python, SQL, R, Bash (Linux), Java, C++ Machine Learning/Statistical Modeling: Data Analysis/Feature engineering (pandas, scipy, numpy, pyspark); Deep Learning RRN/CNN/NCF/NLP(keras,tf), Classification/Regression analysis (sklearn, statsmodels, xgboost), Time-Series(auto.arima, arch, prophet), Recommendation Systems (scikit-surprise, sparkml), Monte Carlo Simulations (rjags), Network Analysis (networkx, gephi). Big Data/Cloud Platforms: Apache Spark, Databricks, Microsoft Azure, Google Cloud, AWS SQL/NoSQL Databases: SQL Server/MySQL/PostgreSQL, InfluxDB, MongoDB Data Visualization/GUI: Matplotlib/Plotly, PowerBI, Dash, Grafana, Tableau, Plotly, Gephi, QT, Streamlit, ggplot.