I am an ambitious 4th-year Data Science & AI student with a strong track record of solving real-world problems through machine learning, computer vision, and NLP. I have delivered impactful solutions in logistics, plant science, and media analytics, often building end-to-end systems including dashboards, predictive models, and cloud-based deployments. I enjoy working on interdisciplinary teams and delivering practical, measurable results. The hands-on experience I gained during internships and projects has helped me grow as a collaborative problem solver adaptable to dynamic environments.

Dominik Szewczyk

I am an ambitious 4th-year Data Science & AI student with a strong track record of solving real-world problems through machine learning, computer vision, and NLP. I have delivered impactful solutions in logistics, plant science, and media analytics, often building end-to-end systems including dashboards, predictive models, and cloud-based deployments. I enjoy working on interdisciplinary teams and delivering practical, measurable results. The hands-on experience I gained during internships and projects has helped me grow as a collaborative problem solver adaptable to dynamic environments.

Available to hire

I am an ambitious 4th-year Data Science & AI student with a strong track record of solving real-world problems through machine learning, computer vision, and NLP. I have delivered impactful solutions in logistics, plant science, and media analytics, often building end-to-end systems including dashboards, predictive models, and cloud-based deployments.

I enjoy working on interdisciplinary teams and delivering practical, measurable results. The hands-on experience I gained during internships and projects has helped me grow as a collaborative problem solver adaptable to dynamic environments.

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Language

English
Fluent
Polish
Fluent
German
Beginner

Work Experience

Data Science Intern at De Rooy Transport & Logistics
June 30, 2025 - August 29, 2025
Built an AI system to predict unexpected pickups and optimize logistics, reducing up to 1500 km of driving per day. Designed a multi-model predictive pipeline (Keras, Random Forest, XGBoost) for forecasting time, location, size, and quantity of pickups. Developed a Streamlit app enabling employees to upload data, train models, and generate route-optimized predictions. Integrated predictions with PTV route planning and scheduled for full deployment in August 2025. Delivered measurable savings in time, cost, and CO2; praised by the company for practical value and impact.

Education

Data Science & Artificial Intelligence at Breda University of Applied Sciences
January 1, 2022 - January 1, 2026
Extended Mathematics Profile at II L O I M. Andrzeja Frycza Modrzewskiego
January 1, 2019 - January 1, 2023

Qualifications

Add your qualifications or awards here.

Industry Experience

Transportation & Logistics, Life Sciences, Media & Entertainment, Energy & Utilities, Education