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Hello, I am Szilárd Ecsenyi, a curious AI/ML engineer with a strong background in data science and distributed systems. I enjoy turning complex data into actionable insights and building scalable software that helps teams make better decisions. I have hands-on experience from research labs to production trading platforms, designing robust data pipelines, and deploying scalable machine learning solutions.\n\nI thrive in collaborative settings, enjoy exploring new technologies such as Python, Scala, Spark, PySpark, Docker, and Kubernetes, and aim to deliver maintainable code while balancing speed and reliability. I am always interested in mentoring others, discussing AI ethics and data governance, and building trustworthy AI systems.…Hello, I am Szilárd Ecsenyi, a curious AI/ML engineer with a strong background in data science and distributed systems. I enjoy turning complex data into actionable insights and building scalable software that helps teams make better decisions. I have hands-on experience from research labs to production trading platforms, designing robust data pipelines, and deploying scalable machine learning solutions.\n\nI thrive in collaborative settings, enjoy exploring new technologies such as Python, Scala, Spark, PySpark, Docker, and Kubernetes, and aim to deliver maintainable code while balancing speed and reliability. I am always interested in mentoring others, discussing AI ethics and data governance, and building trustworthy AI systems.

Ecsenyi Szilárd

Data Scientist, AI Engineer, Full Stack Developer, +3

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Hello, I am Szilárd Ecsenyi, a curious AI/ML engineer with a strong background in data science and distributed systems. I enjoy turning complex data into actionable insights and building scalable software that helps teams make better decisions. I have hands-on experience from research labs to production trading platforms, designing robust data pipelines, and deploying scalable machine learning solutions.\n\nI thrive in collaborative settings, enjoy exploring new technologies such as Python, Scala, Spark, PySpark, Docker, and Kubernetes, and aim to deliver maintainable code while balancing speed and reliability. I am always interested in mentoring others, discussing AI ethics and data governance, and building trustworthy AI systems.…Hello, I am Szilárd Ecsenyi, a curious AI/ML engineer with a strong background in data science and distributed systems. I enjoy turning complex data into actionable insights and building scalable software that helps teams make better decisions. I have hands-on experience from research labs to production trading platforms, designing robust data pipelines, and deploying scalable machine learning solutions.\n\nI thrive in collaborative settings, enjoy exploring new technologies such as Python, Scala, Spark, PySpark, Docker, and Kubernetes, and aim to deliver maintainable code while balancing speed and reliability. I am always interested in mentoring others, discussing AI ethics and data governance, and building trustworthy AI systems.

Available to hire

Hello, I am Szilárd Ecsenyi, a curious AI/ML engineer with a strong background in data science and distributed systems. I enjoy turning complex data into actionable insights and building scalable software that helps teams make better decisions. I have hands-on experience from research labs to production trading platforms, designing robust data pipelines, and deploying scalable machine learning solutions.\n\nI thrive in collaborative settings, enjoy exploring new technologies such as Python, Scala, Spark, PySpark, Docker, and Kubernetes, and aim to deliver maintainable code while balancing speed and reliability. I am always interested in mentoring others, discussing AI ethics and data governance, and building trustworthy AI systems.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Language

Hungarian

Fluent

English

Advanced

Work Experience

AI/ML Engineer at Self-Employed

June 1, 2025 - Present

Developed a new data-driven correlation-shift prediction system that learns how specific events affect inter-company correlation structures and converts these insights into trading signals. Designed a scalable neural architecture combining attention-based news embeddings, company-aware gating, and Fisher-z-stabilized correlation modeling. Implemented a hybrid global–local correlation decomposition significantly reducing model complexity while improving predictive robustness for automated trading. Technologies used: PyTorch, scikit-learn, TensorFlow, NumPy.

Data Scientist at Semilab Semiconductor Physics Laboratory Zrt

July 1, 2023 - May 1, 2025

Evaluated measurement data and provided analytical support through custom Python applications. Applied advanced statistical methods and interpreted results to generate charts and visualizations, helping physicists identify trends and extract insights from complex data sets. Designed scalable data-ingestion and transformation systems enabling distributed and parallel computation with PySpark and Hadoop; built data-processing workflows to improve system responsiveness while maintaining reliability and code quality in production.

Scala Developer at Morgan Stanley

July 1, 2018 - April 1, 2020

Managed real-time computations using immutable data structures to prevent unintended state changes. Contributed to algorithmic implementation of complex business logic, pattern matching, implicit function conversions, and for-comprehensions to express functional flows in Scala-based systems. Provided backend support for real-time trading platforms using a robust, scalable architecture.

Java Developer at ENSO Software Solutions Kft

May 1, 2020 - May 1, 2023

Developed RESTful APIs composed of microservices, deployed using Docker containers and CI/CD pipelines to ensure seamless integration, consistent environment configurations, and efficient resource allocation. Managed database access with JPA and automated schema evolution through custom migration scripts, focusing on reliable data transformations during structural updates. Built resilient, distributed systems using Akka actors to manage back-pressure and process large data streams asynchronously, enabling fault-tolerant communication within a microservice architecture. Applied message queues (e.g., RabbitMQ, Kafka) to decouple components and facilitate scalable, event-driven data flow.

Scala Developer at Morgan Stanley

December 1, 2016 - April 1, 2018

Led development of real-time analytics engine for streaming data using immutable data structures to prevent unintended state changes. Leveraged temporal databases to support safe, time-consistent processing in scenarios involving concurrent modifications and historical data tracking. Contributed to the algorithmic implementation of complex business logic, frequently applying pattern matching, implicit function conversions, and for-comprehensions to express functional flows concisely in Scala-based systems. Provided backend support for real-time, automated trading strategies platforms using the Optimus framework, enabling graph-based branching scenarios in parallel computing environments to handle dynamic, data-intensive execution paths efficiently.