ML Model Development & Optimisation

From classical ML algorithms to cutting-edge deep learning models, we design and fine-tune solutions that deliver high accuracy and efficiency. Our approach includes feature engineering, hyperparameter tuning, and continuous learning and feedback loops to maximise model performance.

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People behind the numbers

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  • Kateryna Stetsiuk

    Kateryna Stetsiuk

    Head of AI Practice

    Kate is the Head of AI Practice at The Dot Collective, helping businesses integrate AI to reduce costs and drive growth.

    With over a decade in AI, Kate has built and scaled AI/ML teams, trained 4,000+ professionals, and led workshops for industry leaders like L’Oréal and BNP Paribas. A recognised speaker at major tech conferences, she also writes for Dataconomy and hosts a YouTube channel on AI for business.

  • Esref Mutlu

    Esref Mutlu

    Senior Data Engineer - Principal

    Esref is the Principal Engineer at The Dot Collective, with over a decade of experience in designing and implementing secure, scalable, and well-governed cloud-native data and machine learning platforms across a variety of industry verticals, including insurance, banking and third sector. His expertise lies in unlocking the power of data, enabling organizations to democratize insights and drive informed decision-making.

  • Vlad Suvorov

    Vlad Suvorov

    Senior Data Engineer

    Vlad is a seasoned Senior Data Engineer specialising in big data solutions. His diverse background equips him to approach projects from multiple angles, effectively bridging the gap between business requirements and technical execution. With several years of leadership experience, Vlad is adept at prioritising tasks and driving projects to successful completion. He is passionate about leveraging big data to empower organisations with data-driven insights and decision-making.

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