pawlowskipawel

Data Scientist

https://talent.gravityer.com/pawlowskipawel

Member since June 29, 2026

Key Strengths

Demonstrated proficiency in Python for data science and machine learning tasks.
Extensive experience with various Kaggle competitions, indicating practical application of ML techniques.
Familiarity with large language models (LLMs) and natural language understanding (NLU) through personal projects.
Experience with deep learning frameworks and concepts, including transformers.
Exposure to MLOps related tools like Dockerfile and Shell scripting.

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

MT-LLM-NLU

March 27, 2024 – April 12, 2024

Repository for code related to "LLM-Based Machine Translation for Expansion of Spoken Language Understanding Systems to New Languages" publication.

View Project

whisper-finetuning

June 23, 2023 – June 23, 2023

whisper-finetuning — GitHub repository

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kaggle-benetech-making-graphs-accessible

June 21, 2023 – June 21, 2023

kaggle-benetech-making-graphs-accessible — GitHub repository

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kaggle-rsna-breast-cancer-detection

March 28, 2023 – March 28, 2023

kaggle-rsna-breast-cancer-detection — GitHub repository

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transformer-from-scratch

May 29, 2022 – June 6, 2022

transformer-from-scratch — GitHub repository

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kaggle_patent_phrase_matching

April 23, 2022 – June 6, 2022

kaggle_patent_phrase_matching — GitHub repository

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kaggle_happy_whales_competition

March 16, 2022 – June 6, 2022

kaggle_happy_whales_competition — GitHub repository

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invoices

June 16, 2021 – August 2, 2021

synthetic invoices data

View Project

Key Strengths

Demonstrated proficiency in Python for data science and machine learning tasks.
Extensive experience with various Kaggle competitions, indicating practical application of ML techniques.
Familiarity with large language models (LLMs) and natural language understanding (NLU) through personal projects.
Experience with deep learning frameworks and concepts, including transformers.
Exposure to MLOps related tools like Dockerfile and Shell scripting.

Cultural Fit Analysis

The candidate's projects are primarily personal and competition-focused, indicating a strong drive for self-learning and practical application. However, the lack of team-based or professional project experience makes it difficult to fully assess cultural fit within a collaborative work environment. The projects align well with a Data Scientist role, particularly in NLP and computer vision domains.

Soft Skills & Operational Fit

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

pawlowskipawel

Key Strengths

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit