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Principal AI Scientist | Computer Science Engineer | PhD | RL, LLM, Deep Learning | AI System Architecture & Production-Scale ML
AI Scientist and Computer Science engineer with 20+ years of experience spanning research, software engineering, and large-scale machine learning systems. PhD in Data Mining and Machine Learning from the University of Amsterdam. Specializes in AI, software architecture, and system design for scalable, production-grade solutions. Skilled in machine learning—including classical ML and deep learning—reinforcement learning, large language models, and end-to-end ML platforms. Experienced in architecting complex intelligent systems from research prototypes to robust, operational infrastructure. Focused on building robust, scalable ML systems with long-term impact and technical ownership.
University of Amsterdam
Doctor of Philosophy (Ph.D.), Artificial Intelligence
January 1, 2003 – January 1, 2007
Vrije Universiteit Amsterdam (VU Amsterdam)
Master's Degree, Artificial Intelligence
January 1, 2002 – January 1, 2003
Technical University of Cluj Napoca
Engineer's Degree, Computer Science
January 1, 1998 – January 1, 2003
National College "Horea, Closca si Crisan" Alba Iulia, Romania
High School Diploma, Mathematics and Physics
January 1, 1994 – January 1, 1998
VodafoneZiggo
Senior Data Scientist / AI Engineer
April 1, 2019 – Present
The Randstad, Netherlands · Hybrid
Quby - outsmarting energy
Senior Data Scientist, Machine Learning and (Big) Data Science solutions
May 1, 2016 – April 1, 2019
Amsterdam
Global Collect, LeasePlan, Heineken, KPN, Shell, Essent, APG
Data Science and Software Engineering Consultant
July 1, 2014 – May 1, 2016
(via Accenture)
Accenture
Data Science Consultant
February 1, 2014 – May 1, 2016
The Randstad, Netherlands
Philips
Consultant
February 1, 2014 – June 1, 2014
(via Accenture)
SKF Engineering & Research Centre
Consultant/ Software Engineer
October 1, 2011 – January 1, 2014
(via Logica/CGI)
ING
Consultant
April 1, 2010 – June 1, 2011
(via Logica/CGI)
Alliander
Consultant/ Software Engineer
January 1, 2009 – January 1, 2010
(via Logica/CGI)
Nuon
Consultant/ Software Engineer
January 1, 2008 – January 1, 2009
(via Logica/CGI)
CGI Nederland
Experienced Software Engineer / Consultant
November 1, 2007 – January 1, 2014
University of Amsterdam, Academic Medical Center
Ph.D. Researcher
January 1, 2003 – January 1, 2007
The Randstad, Netherlands
Reinforcement Learning Specialization
University of Alberta, Alberta Machine Intelligence Institute
June 24, 2026 – Present
A Complete Reinforcement Learning System (Capstone)
University of Alberta, Alberta Machine Intelligence Institute
June 24, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 24, 2026 – Present
Fundamentals of Reinforcement Learning
University of Alberta, Alberta Machine Intelligence Institute
June 24, 2026 – Present
Sample-based Learning Methods
University of Alberta, Alberta Machine Intelligence Institute
June 24, 2026 – Present
Prediction and Control with Function Approximation
University of Alberta, Alberta Machine Intelligence Institute
June 24, 2026 – Present
DevOps Engineering on AWS
AWS Training Online
June 24, 2026 – Present
Architecting on AWS - Accelerator
AWS Training Online
June 24, 2026 – Present
Sequence Models
Coursera
June 24, 2026 – Present
Convolutional Neural Networks
Coursera
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a strong focus on advanced AI and data science, aligning well with roles requiring innovation and deep technical expertise. The diverse industry experience (telecom, energy, finance, consulting) indicates adaptability. However, the target role of 'Data Analyst' might be a mismatch for a candidate with a Ph.D. and extensive senior-level Data Scientist/AI Engineer experience, potentially leading to underutilization of their advanced skills and a lack of long-term engagement if the role is not sufficiently challenging.
Soft Skills & Operational Fit
The candidate's extensive consulting background suggests adaptability, problem-solving skills, and the ability to work across various business contexts. The descriptions of advising business and supporting product teams indicate strong communication and collaboration skills. However, without specific psychometric test results, a definitive assessment of work attitude, stress handling, and team collaboration is not possible.