Position: Data Scientist, Data Analyst
Category: Data Science
English level: upper
Years of experience: 6

As a co-founder of Equipmetry, a fleet management system, I have leveraged the most effective fleet management methodologies and Machine Learning algorithms to provide companies with a powerful solution for managing their fleets.
The system has helped numerous companies to optimize their fleet operations and reduce costs.


One of our notable achievements has been optimizing spare parts and consumables spends, resulting in a
20% decrease in long-tail spending.
Decreased emergency repairs by 30%
Improved the fleet repair process from 61 days to just 30 days.
Implemented Predictive and Preventive Maintenance methodologies and Job Optimization algorithms, resulting in a
significant decrease in unplanned downtime.


Through Equipmetry, I have demonstrated my ability to leverage cutting-edge technology and Machine Learning, Business
Analysis methodologies to deliver value to companies across industries. I am confident in my ability to continue driving measurable results and improving business outcomes for my clients.

Developed a sophisticated system for forecasting and optimizing schedules for workers in companies with shift-based schedules, using a combination of machine learning and linear programming. I successfully implemented this system at Magnum Cash & Carry LLC, the largest chain of supermarkets in Kazakhstan with approximately 80 locations Decreased spending costs by approximately 25%, resulting in savings of $3 million per year.
Reduced clients' waiting times by approximately 40%, from 30 minutes to just ~15 minutes.
As a Data Scientist, Data Analyst, and Machine Learning Engineer with 6 years of experience, I have a successful history of working across a variety of industries, including manufacturing, industrial, retail, telecommunications, banks, and startups.
My work has focused on leveraging Data Science, Optimization methods, and Data Analytics to drive business outcomes and improve customer experiences.


Developed and implemented ML algorithms that decreased emergency repairs by 30%, resulting in significant cost savings and increased operational efficiency. Utilized optimization methods to improve waiting times for clients, resulting in a 40%
reduction in wait time (from 30 minutes to 16-18 minutes) across 85 departments in hypermarkets.