Ex. Software Engineer at Paidax Limited
New York, United States
Bauyrzhan Beisenbayev
Council Member
Bauyrzhan Beisenbayev is a software engineer and data infrastructure specialist with over three years of professional experience building enterprise systems, cloud-native platforms, and AI-driven applications across Kazakhstan and the United States. Based in Brooklyn, New York, he has established himself as a technical contributor focused on backend architecture, distributed systems, and scalable data platforms that support digital transformation in both startup and enterprise environments.
From August 2024 to October 2024, Bauyrzhan Beisenbayev served as a Software Engineer at Paidax Limited, a private next-generation investment platform startup in Astana, Kazakhstan. In this role, he developed core APIs and backend services using .NET Core and Web API, contributing directly to the platform's cloud-native and distributed system architecture built on Orleans, Docker, Kubernetes, and Google Cloud. He worked extensively with PostgreSQL, Oracle, ElasticSearch, and RabbitMQ to support scalable and reliable financial workflows, and played a critical role in technical architecture decisions during the company's early-stage development.
Prior to that, from October 2022 to May 2023, Bauyrzhan Beisenbayev held the position of IT Programmer at MegaElectron LLP in Taraz, Kazakhstan, where he led the modernization of enterprise IT infrastructure supporting ERP, accounting, warehouse, and production systems. He conducted a comprehensive system audit, optimized databases, redesigned API integrations, and improved network and monitoring configuration using .NET Core and MS SQL. His work resulted in approximately 20% faster internal request processing, a 23% increase in employee efficiency, and a significant reduction in system failures—outcomes that proved critical to company-wide operational stability.
Bauyrzhan Beisenbayev has authored three peer-reviewed research articles published in December 2025. His first publication, "Using Explainable AI (XAI) Algorithms to Interpret the Results of Analytical Models in Management Decision-Making," appeared in the Modern American Journal of Engineering, Technology, and Innovation and examines the application of explainable artificial intelligence techniques such as LIME and SHAP for interpreting machine learning model outputs to improve transparency in management decision-making and data-driven business analytics. His second article, "Methods of Detecting Anomalies in Business Data Using Machine Learning: A Comparative Review of Models and Practical Cases," was published in the American Journal of Technology and Applied Sciences and presents a comparative analysis of machine learning methods for anomaly detection in business data, including statistical, density, cluster, neural network, and hybrid techniques, with practical case studies relevant to fraud detection, data quality assurance, and operational process monitoring. His third publication, "Application of Generative AI to Automate Analytical Reports: Opportunities, Risks, and Quality Control Methods," appeared in the American Journal of Pedagogical and Educational Research and discusses modern approaches to using generative models for automating analytical report generation, evaluating practical benefits, inherent risks including hallucinations and data leakage, and proposing quality control methods and organizational strategies for reliable corporate analytics.
From August 2024 to October 2024, Bauyrzhan Beisenbayev served as a Software Engineer at Paidax Limited, a private next-generation investment platform startup in Astana, Kazakhstan. In this role, he developed core APIs and backend services using .NET Core and Web API, contributing directly to the platform's cloud-native and distributed system architecture built on Orleans, Docker, Kubernetes, and Google Cloud. He worked extensively with PostgreSQL, Oracle, ElasticSearch, and RabbitMQ to support scalable and reliable financial workflows, and played a critical role in technical architecture decisions during the company's early-stage development.
Prior to that, from October 2022 to May 2023, Bauyrzhan Beisenbayev held the position of IT Programmer at MegaElectron LLP in Taraz, Kazakhstan, where he led the modernization of enterprise IT infrastructure supporting ERP, accounting, warehouse, and production systems. He conducted a comprehensive system audit, optimized databases, redesigned API integrations, and improved network and monitoring configuration using .NET Core and MS SQL. His work resulted in approximately 20% faster internal request processing, a 23% increase in employee efficiency, and a significant reduction in system failures—outcomes that proved critical to company-wide operational stability.
Bauyrzhan Beisenbayev has authored three peer-reviewed research articles published in December 2025. His first publication, "Using Explainable AI (XAI) Algorithms to Interpret the Results of Analytical Models in Management Decision-Making," appeared in the Modern American Journal of Engineering, Technology, and Innovation and examines the application of explainable artificial intelligence techniques such as LIME and SHAP for interpreting machine learning model outputs to improve transparency in management decision-making and data-driven business analytics. His second article, "Methods of Detecting Anomalies in Business Data Using Machine Learning: A Comparative Review of Models and Practical Cases," was published in the American Journal of Technology and Applied Sciences and presents a comparative analysis of machine learning methods for anomaly detection in business data, including statistical, density, cluster, neural network, and hybrid techniques, with practical case studies relevant to fraud detection, data quality assurance, and operational process monitoring. His third publication, "Application of Generative AI to Automate Analytical Reports: Opportunities, Risks, and Quality Control Methods," appeared in the American Journal of Pedagogical and Educational Research and discusses modern approaches to using generative models for automating analytical report generation, evaluating practical benefits, inherent risks including hallucinations and data leakage, and proposing quality control methods and organizational strategies for reliable corporate analytics.
Bauyrzhan Beisenbayev has been featured in several industry publications as a technical expert. In May 2024, his insights appeared in RUAinform.com in an article titled "The Era of Data: Which Systems Can Withstand Digital Growth and What Modern Analysts Must Understand," exploring the importance of robust data architectures and scalable systems in the digital age. In October 2025, he was referenced in inAlmaty.kz in a feature article titled "Generation of Data: Why Data Analysts & BI Become the Profession of the Future," highlighting trends in data analytics and business intelligence and the evolving importance of data-driven decision-making. In August 2023, his expertise contributed to an industry feature in Innov.ru titled "Crisis of Trust in Data: Why Companies Struggle to Make Correct Decisions Even with Advanced BI Infrastructure," discussing systemic issues such as weak data architecture, inconsistent transactions, and low data quality that prevent organizations from making accurate business decisions despite modern BI investments.
Bauyrzhan Beisenbayev has received multiple awards recognizing his technical excellence and project work. In October 2024, he received the Best Project Award in IT Innovations in Logistics from Astana Hub for developing and presenting the best IT project in the field of logistics, recognized for technological innovation, practical applicability, and contribution to digital solutions in logistics. In 2018, he earned a Bronze Medal at the INFOMATRIX Asia International Competition, an international project-based competition recognizing technical excellence, innovation, and effective project implementation among teams from multiple countries. In 2019, he received a Second Place Diploma at the ACM ICPC Quarterfinals as part of a university student team, a globally recognized competitive programming championship evaluating algorithmic thinking, problem-solving skills, and programming proficiency under strict time constraints. In December 2020, he received an Honorable Mention Certificate of Achievement at the ICPC Northern Eurasia Finals, one of the most prestigious global competitive programming competitions, recognizing high-level performance at the regional finals.
Bauyrzhan Beisenbayev has received multiple awards recognizing his technical excellence and project work. In October 2024, he received the Best Project Award in IT Innovations in Logistics from Astana Hub for developing and presenting the best IT project in the field of logistics, recognized for technological innovation, practical applicability, and contribution to digital solutions in logistics. In 2018, he earned a Bronze Medal at the INFOMATRIX Asia International Competition, an international project-based competition recognizing technical excellence, innovation, and effective project implementation among teams from multiple countries. In 2019, he received a Second Place Diploma at the ACM ICPC Quarterfinals as part of a university student team, a globally recognized competitive programming championship evaluating algorithmic thinking, problem-solving skills, and programming proficiency under strict time constraints. In December 2020, he received an Honorable Mention Certificate of Achievement at the ICPC Northern Eurasia Finals, one of the most prestigious global competitive programming competitions, recognizing high-level performance at the regional finals.