Background

As a consultant in the AI risk unit at EY, I assist financial institutions in mitigating model risk associated with their AI/ML-based models, primarily within the anti-financial crime domain. My role involves conducting technical reviews, performing experiments, and analyzing these models.

Prior to transitioning to the financial industry in 2018, I worked as a computer science researcher, doing a PhD and spending six years as a postdoctoral researcher. During my PhD, I specialized in probabilistic logic programming. As a postdoc, my work revolved around applied data analytics of genetics data, emphasizing high-performance computing, data quality control, imputation, data privacy, and statistical testing.

From 1999 to 2008, I worked as a software developer and cybersecurity consultant in various contexts. I held positions in early-stage startups, SMEs, and multinational corporations, and also operated as an independent consultant in my own company for several years.

Motivation

I have been inspired and guided by a diverse set of thoughtful and kind people throughout my carrier. I would like to pay it forward.

On the other hand, I seek not only to guide and inspire, but also be inspired. I expect mentoring to a two-way street, where you not only impart your expertise but also learn from your mentees and this is a large part of motivation. Explaining concepts, answering questions, and providing guidance forces you to stay up-to-date with the latest trends and advancements in the field of data science.

Finally, I hope that the relationship formed can be open up doors for both you and me, wherever our future carriers might take us.

Skills, expertise, and interests

• Data science
• Data analytics
• Data visualisation
• Data mining
• Big data
• Data management
• Time series analysis
• Text analysis
• Statistical and data modelling
• Machine learning
• Deep learning
• Artificial intelligence
• Natural language processing (NLP)
• Causality and explainability
• Bioinformatics
• Computational science
• High-performance computing
• Statistics and mathematics
• Economics, finance, and business
• Consulting
• Software engineering
• Career planning or change
• Work-life balance
• Teamwork

Programming languages and software

• Python
• R
• SQL
• Java
• Scala
• JavaScript
• C++/C
• Julia
• Ruby
• PHP
• Perl
• Shell Scripting (e.g., Bash)
• Apache Spark