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Hüseyin Okan DemirHD
Open to opportunities

Hüseyin Okan Demir

@hseyinokandemir

I build scalable game platforms and turn player data into revenue and engagement gains.

Austria
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What I'm looking for

I'm looking to build scalable, data-informed products where I can combine backend engineering, analytics, and machine learning to improve user experiences and business outcomes.

At Board Labs, I engineered and deployed a high-performance Golang server for a multiplayer board game serving over 10,000 monthly active players. I built real-time matchmaking, tournament management, geolocation services, and secure multi-currency payments with Xsolla and Stripe.

I implemented observability with OpenTelemetry and Uptrace to support availability and performance, while using goroutines and channels to solve complex concurrency challenges.

Previously at Zynga, I analyzed High Heels player data and proposed features that increased revenue by 15%. I also helped design a K-Means-based dynamic difficulty system that raised engagement by 10% and developed user-progression analysis using graph and tree data structures.

My work also includes deep-learning research for Ethereum smart-contract vulnerability detection, achieving 96% accuracy and reducing analysis time by 80% against traditional static analyzers. I enjoy applying software engineering, data analysis, and machine learning to products people use.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

Johannes Kepler University Linz logoJL

Johannes Kepler University Linz

Master of Science, Artificial Intelligence

2026 - 2028

Pursuing a Master of Science in Artificial Intelligence at Johannes Kepler University Linz from 2026 to 2028.

Izmir Institute of Technology logoIT

Izmir Institute of Technology

Bachelor of Science, Electronics and Communication Engineering

2018 - 2023

Grade: 3.16 / 4.00

Completed a Bachelor of Science in Electronics and Communication Engineering with a GPA of 3.16/4.00. Thesis focused on blockchain vulnerability detection using LSTM.

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