aliutov

● Led development of a tool for a US oil company to estimate drilling rig liquid compositions, enhancing drilling efficiency. Employed various ML models for classification and regression tasks. Led a Junior Data Scientist and presented model analytics with recommendations. ● Created an online tool for a US oil company to detect anomalous patterns in drilling equipment time-series data. Designed an anomaly detection model and integrated with Azure. Led an Intern Data Scientist and researched various detection methods. ● Developed an internal tool for a US oil company to preprocess large parquet files from Azure Data Lake, offering metadata reading, data statistics, and outlier detection. Provided a tutorial on its usage with PySpark for colleagues handling Big Data. ● Transitioned a drilling safety system for a US oil company from MATLAB to Python, achieving a 10x speed increase. Evaluated PySpark vs. Python performance, re-implemented the system in Python, and integrated with Azure Data Lake in Azure Databricks.

● Developed an internal tool using Python and PostgreSQL to segment customers for targeted marketing and prioritized support. Extracted data, and applied clustering algorithms, and factor analysis (PFM) to create distinct customer groups, resulting in enhanced sales strategies. ● Utilized Python to extract data from PostgreSQL, forecasted future profit using ARIMA, and subsequently analyzed the model's positive impact on profit.

● Built a Python tool to recommend driving modes, improving user experience and safety, and helped enhance mode-switching and engagement. ● Developed a tool to predict fuel usage on different routes, considering both paid and free roads, and used Python, XGBoost, and Flask, and created a user-friendly testing webpage for practical use.

● Collaborated with a Senior Data Scientist at a bank to build a time-series prediction model using ARIMA in SAS Miner. The model was designed to forecast the default rate for the PI segment of bank clients. These predictions were instrumental in shaping bank savings decisions.