Open to opportunities

Antonio Parunov

@antonioparunov

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Data scientist with expertise in machine learning and AI systems.

Croatia

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What I'm looking for

I am looking for opportunities that allow me to innovate and lead projects in data science, with a focus on collaborative environments that value creativity and continuous learning.

I'm a data scientist with over three years of experience specializing in machine learning, big-data engineering, and the development of end-to-end AI systems. My most notable achievement includes the creation of Apollo, an AI ad-placement optimization engine that processes over 1 petabyte of data weekly. This project not only contributed to a successful $10 million Series B funding round but also resulted in a significant 20% reduction in operational costs.

Throughout my career, I have honed my skills in various domains, including recommendation systems, computer vision, and natural language processing. My academic background includes a Master’s degree in Physics from the University of Zagreb, where I focused on numerical methods and machine learning. I have also co-authored a publication in Acta Crystallographica B and achieved high rankings in several data science competitions, showcasing my commitment to excellence and innovation in the field.

Experience

Work history, roles, and key accomplishments

Current

Data Scientist

Current

All Eyes on Screens

Oct 2022 - Present (2 years 8 months)

Led the end-to-end development of Apollo, an AI ad-placement optimization engine processing data from millions of users. Built custom neural networks achieving state-of-the-art performance metrics at reduced operational cost, and designed and deployed scalable data pipelines, automating CI/CD and MLOps. Played an instrumental role in helping the company secure a $10M Series B funding round.

AI Machine Learning Neural Networks Data Pipelines CI CD MLOps Python AWS Spark PostgreSQL

Junior Data Scientist

Cloudonia

Nov 2021 - Oct 2022 (11 months)

Developed ShelfXplorer, a computer vision application for automatic retail shelf analysis. Enhanced the product by developing key features such as shelf detection, article-size estimation, and OCR for price tags. Delivered proof-of-concepts, collaborating closely with stakeholders.

Computer Vision Python Machine Learning Image Processing OpenCV Stakeholder Management Data Analysis

Education

Degrees, certifications, and relevant coursework

University of Zagreb

M.Sc. Physics, Physics

Activities and societies: Graduate researcher and teaching assistant in computational materials science (2019–2022)

Focused on numerical methods and machine learning. Thesis: Transfer Learning of Interatomic Potentials: From Molecules to Crystals – applied graph neural networks to accelerate drug discovery. Served as a graduate researcher and teaching assistant in computational materials science from 2019–2022.