Valentin Pardo

Data Engineer

Tandil, Buenos Aires Province, Argentina7 mos experience

Key Highlights

Developed a computer vision pipeline for sports analytics.
Improved AI model recall by 15% through advanced training techniques.
Strong foundation in data engineering and machine learning.

Stackforce AI infers this person is a Data Engineer with a focus on Artificial Intelligence and Computer Vision in the Sports Analytics domain.

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Skills

Core Skills

Data EngineeringArtificial Intelligence (ai)Computer Vision

Other Skills

Python (Programming Language)EngineeringYOLOv5OpenCVTensorFlowKerasPythonPandasNumPyDesign PatternsSoft Skills TrainingSoft SkillsNeo4jHugging Face ProductsTransformers

About

Hello! I'm Valentin, a Computer Engineering student about to graduate, passionate about turning data and algorithms into real-world impact. I am now focused on continuing my professional journey in Artificial Intelligence, Data Science, Machine Learning, Data Engineering, or Python development. Through my academic and project experience, I built strong foundations in computer science, advanced algorithms, and software engineering, while developing hands-on solutions involving Python, Data Science, and automation. I enjoy tackling complex challenges and continuously learning new tools to stay at the forefront of technology. Outside of technology, I find balance in sports, reading, and drawing—activities that nurture both discipline and creativity. I am eager to contribute to a collaborative team where I can apply my skills, keep growing, and help drive innovation through data-driven solutions. Let’s connect!

Experience

7 mos

Total Experience

Average Tenure

Current Experience

Ig networks

Data Engineer

Nov 2025 – Present · 7 mos · Tandil, Buenos Aires Province, Argentina · Remote

Working in the Automation team as a Data Engineer with AI focus

Data EngineeringPython (Programming Language)

Mol solutions

2 roles

Junior AI Engineer

Mar 2025 – Nov 2025 · 8 mos

Collaborated on computer vision and backend automation projects, integrating AI solutions into production-level workflows.
Designed and deployed an end-to-end computer vision pipeline for tennis match analysis, integrating video preprocessing, object detection, and automated reporting.
Implemented YOLOv5 + OpenCV models to detect players and balls with 89% accuracy, reducing manual annotation time by 70%.
Trained and validated CNN and LSTM models with TensorFlow/Keras, improving recall by 15% compared to baseline models.
Built reproducible Python (Pandas, NumPy) pipelines, ensuring scalability and data integrity across multiple video datasets.
Produced technical documentation and presented insights to both technical and non-technical stakeholders, facilitating adoption of AI-driven analytics in production workflows.

Artificial Intelligence (AI)Engineering