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I'm Bogdan Vedernikovai, a Machine Learning Engineer with 5+ years of industry experience and 3+ years focused on applied ML. I design and deploy end-to-end ML systems, including deep learning pipelines, computer vision, and GenAI automation.\n\nMy work spans sports analytics at Athlete Focus and energy/logistics optimization at Gazprom Neft. I built production CV pipelines (YOLOv8), integrated NetVLAD CNN with LLM-based feedback, and created Excel-based forecasting for maritime routing, delivering measurable efficiency and cost savings while mentoring junior engineers.…I'm Bogdan Vedernikovai, a Machine Learning Engineer with 5+ years of industry experience and 3+ years focused on applied ML. I design and deploy end-to-end ML systems, including deep learning pipelines, computer vision, and GenAI automation.\n\nMy work spans sports analytics at Athlete Focus and energy/logistics optimization at Gazprom Neft. I built production CV pipelines (YOLOv8), integrated NetVLAD CNN with LLM-based feedback, and created Excel-based forecasting for maritime routing, delivering measurable efficiency and cost savings while mentoring junior engineers.

Bogdan Vedernikovai

Data Analyst, Data Scientist, AI Engineer, +4

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I'm Bogdan Vedernikovai, a Machine Learning Engineer with 5+ years of industry experience and 3+ years focused on applied ML. I design and deploy end-to-end ML systems, including deep learning pipelines, computer vision, and GenAI automation.\n\nMy work spans sports analytics at Athlete Focus and energy/logistics optimization at Gazprom Neft. I built production CV pipelines (YOLOv8), integrated NetVLAD CNN with LLM-based feedback, and created Excel-based forecasting for maritime routing, delivering measurable efficiency and cost savings while mentoring junior engineers.…I'm Bogdan Vedernikovai, a Machine Learning Engineer with 5+ years of industry experience and 3+ years focused on applied ML. I design and deploy end-to-end ML systems, including deep learning pipelines, computer vision, and GenAI automation.\n\nMy work spans sports analytics at Athlete Focus and energy/logistics optimization at Gazprom Neft. I built production CV pipelines (YOLOv8), integrated NetVLAD CNN with LLM-based feedback, and created Excel-based forecasting for maritime routing, delivering measurable efficiency and cost savings while mentoring junior engineers.

Available to hire

I’m Bogdan Vedernikovai, a Machine Learning Engineer with 5+ years of industry experience and 3+ years focused on applied ML. I design and deploy end-to-end ML systems, including deep learning pipelines, computer vision, and GenAI automation.\n\nMy work spans sports analytics at Athlete Focus and energy/logistics optimization at Gazprom Neft. I built production CV pipelines (YOLOv8), integrated NetVLAD CNN with LLM-based feedback, and created Excel-based forecasting for maritime routing, delivering measurable efficiency and cost savings while mentoring junior engineers.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Data Analyst at Athlete Focus

September 1, 2022 - November 12, 2025

Led development of analytics systems and machine learning models used by coaches to optimize training decisions and track player performance. Owned Python ETL pipeline pulling data from GPS tracking devices, heart rate monitors, and match statistics platforms into PostgreSQL database on AWS, processing data from 3 teams across 50+ training sessions and 30+ competitive matches daily. Built 5 dashboards showing workload trends, injury risk indicators, and tactical patterns. Developed clustering models for 40+ players and implemented time-series forecasting with Prophet and LSTM to predict fatigue thresholds; deployed YOLOv8 computer vision pipeline for automated highlight reels; created automated player feedback tool using OpenAI API.

Data Analyst at Gazprom Neft

August 1, 2022 - August 1, 2022

Led development of Excel-based forecasting models combining weather API data and shipping schedules used by maritime operations for route planning across 12-vessel oil tanker fleet. Performed UI/UX analysis of internal logistics platform used by 200+ employees to identify friction points and inform redesign. Improved data quality by resolving 15+ reporting errors affecting quarterly shipment reports (500+ shipments). Built 7 Excel templates using Power Query and VBA for weekly status reports. Conducted correlation analyses between weather conditions and delays across 100+ routes; collaborated with UI/UX designers and backend developers to redesign workflows; documented 150+ data fields for onboarding.

DATA ANALYST at Gazprom Neft

June 1, 2020 - August 1, 2022

Analyzed logistics operations and built forecasting models to support maritime route planning across a 12-vessel tanker fleet in 5 zones. Developed Excel forecasting models combining weather data and schedules; produced 7 Excel reports with Power Query and VBA used by operations managers weekly. Conducted UI/UX analysis of internal logistics platform, resolving 15+ reporting errors affecting shipments (500+ shipments). Performed correlation analyses between weather and delays across 100+ routes; informed risk protocols. Created data documentation for 150+ fields and collaborated with UI/UX designers and backend developers to redesign workflows.

MACHINE LEARNING ENGINEER at Athlete Focus

September 1, 2022 - Present

Led end-to-end computer vision pipeline to automatically generate personalized highlight reels from 90–120 minute match videos, including detection, tracking, re-ID, event detection, and video assembly; fine-tuned YOLOv8 achieving [email protected]=0.95 and 90%+ IDF1 stability; optimized real-time inference on Nvidia T4 to sustain 30+ FPS for 720p–4K streams; integrated ByteTrack for multi-object tracking and a NetVLAD-based action classifier; integrated OpenAI API to produce coach-style feedback; automated daily processing enabling 10+ highlights per day and estimated $150k annual savings.

DATA SCIENTIST at Gazprom Neft

June 1, 2020 - August 1, 2022

Led Excel forecasting models combining weather data and shipping schedules for a 12-vessel tanker fleet; performed correlation analysis between weather and delays; conducted UI/UX analysis of internal logistics platform and contributed to redesign; built 7 Excel reporting templates and created data documentation to onboard analysts; resolved backend data quality issues affecting quarterly shipment reports.