Pavlos Dais

Data Scientist

https://talent.gravityer.com/pavlos-dais

Computer Science| NKUA

Member since June 27, 2026

Key Strengths

Strong foundational knowledge in C++ for data structures and algorithms, as evidenced by projects like 'Abstract-Data-Types' and 'Memory-Allocators'.
Demonstrated interest and practical experience in Artificial Intelligence and Machine Learning, including Reinforcement Learning (MountainCar-v0) and NLP (Deep-Learning-NLP).
Experience with A* search algorithm ('n-puzzle') and adversarial attacks ('PriSM'), indicating problem-solving capabilities in AI.
Exposure to Python for AI/ML projects, aligning with common Data Scientist toolsets.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards personal, self-driven learning and development in computer science fundamentals and AI. The diversity of projects, from low-level memory management to high-level deep learning applications, suggests a curious and proactive individual. The current role as 'Data Scientist' at 'Computer Science| NKUA' aligns directly with the target role, indicating a clear career path. However, without more details on team collaboration or project methodologies, a comprehensive cultural fit assessment is limited.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights into logical reasoning, work attitude, stress handling, or team collaboration.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

PriSM

August 2, 2025 – Present

[TMLR'26] PriSM: Prior-Guided Search Methods for Query Efficient Black-Box Adversarial Attacks

View Project

MountainCar-v0

March 20, 2025 – April 29, 2025

Application of Reinforcement Learning algorithms (DQN,DRQN,PPO,A2C) to gym's MountainCar-v0

View Project

Deep-Learning-NLP

April 5, 2024 – September 27, 2024

Deep learning for Natural Language Processing (FNNs, RNNs, BERT)

View Project

Memory-Allocators

August 23, 2023 – August 25, 2023

A set of custom memory allocators

View Project

Travel-Agency-Database

June 8, 2023 – June 8, 2023

A database schema, queries and a simple website interface for a travel agency

View Project

Miru

March 11, 2023 – July 30, 2023

UCI chess engine

View Project

ai-berkeley

March 3, 2023 – March 3, 2023

My solutions to projects 1, 2 & 3 of Berkeley's AI course

View Project

Abstract-Data-Types

May 24, 2022 – October 3, 2023

A set of efficient data structures in C, created in a generic way

View Project

n-puzzle

April 7, 2022 – April 24, 2023

Classic n-puzzle problem solver using A* search

View Project

Quoridor

January 9, 2022 – April 24, 2023

A terminal implementation of the game Quoridor with an engine

View Project

Key Strengths

Strong foundational knowledge in C++ for data structures and algorithms, as evidenced by projects like 'Abstract-Data-Types' and 'Memory-Allocators'.
Demonstrated interest and practical experience in Artificial Intelligence and Machine Learning, including Reinforcement Learning (MountainCar-v0) and NLP (Deep-Learning-NLP).
Experience with A* search algorithm ('n-puzzle') and adversarial attacks ('PriSM'), indicating problem-solving capabilities in AI.
Exposure to Python for AI/ML projects, aligning with common Data Scientist toolsets.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The psychometric test score is 0, providing no insights into logical reasoning, work attitude, stress handling, or team collaboration.

Pavlos Dais

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit