Vladislav Zamkovoy

Data Scientist

https://talent.gravityer.com/vladislav-zamkovoy

NetherlandsMember since June 29, 2026

Key Strengths

Demonstrated proficiency in Python, a core language for Data Science.
Extensive experience with Jupyter Notebooks for data exploration and model development.
Projects indicate exposure to Machine Learning (LLM, Reinforcement Learning) and graph-structured data problems, relevant for a Data Scientist role.
Experience with Dockerfiles suggests an understanding of containerization for reproducible environments.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and demonstrate a strong interest in data science and machine learning. However, the lack of team-based projects or professional experience makes it difficult to assess cultural fit comprehensively. The projects are diverse within the data science domain, but the absence of broader industry exposure limits the assessment of adaptability to different organizational cultures.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

GFDRR

January 29, 2026 – Present

Unified modular engine for solving complex logistical problems on graph-structured data.

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PermutationsLLM

January 25, 2026 – Present

LLM-based Permutation Algorithm Generator

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genai-accelerator

December 25, 2025 – Present

A GenAI-powered compliance tool for analyzing suspicious transaction comments, built with Zero Trust architecture principles.

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permutations_RL

April 27, 2025 – June 13, 2025

permutations_RL — GitHub repository

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streamlit-exam-form-app

December 16, 2024 – Present

streamlit-exam-form-app — GitHub repository

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GCT-TTE

November 3, 2022 – January 14, 2024

GCT-TTE algorithm & dedicated application

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TransTTE_demo

February 14, 2022 – April 6, 2023

TransTTE_demo — GitHub repository

View Project

Key Strengths

Demonstrated proficiency in Python, a core language for Data Science.
Extensive experience with Jupyter Notebooks for data exploration and model development.
Projects indicate exposure to Machine Learning (LLM, Reinforcement Learning) and graph-structured data problems, relevant for a Data Scientist role.
Experience with Dockerfiles suggests an understanding of containerization for reproducible environments.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Vladislav Zamkovoy

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit