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Lead Data/AI Scientist at F-Secure Corporation
I'm a Lead Data Scientist in F-Secure's Platform Protection unit developing machine learning systems that help protect users from malicious activity online. My primary focus is the design, development, and deployment of end-to-end machine learning solutions, from data collection and feature engineering through to model training, production deployment, and monitoring. I enjoy working across the full lifecycle of ML systems and turning research and data into reliable products that deliver measurable impact. Before joining F-Secure, I worked as a Data Scientist at Unity Ads (Helsinki) and Booking.com (Amsterdam), applying machine learning and data science to large-scale consumer products in the areas of user-level ad conversion, post-app-install user value prediction, and customer lifetime value. I have a PhD in Computational Physics from Trinity College Dublin, awarded in 2016. My background in scientific computing and quantitative modelling continues to shape how I approach complex problems in machine learning, data engineering, and analytics.
Trinity College Dublin
Doctor of Philosophy (Ph.D.), Computational & Mathematical Physics
January 1, 2012 – January 1, 2016
Lancaster University
M.Phys, Theoretical Physics
January 1, 2006 – January 1, 2010
F-Secure Corporation
Lead Data/AI Scientist
April 1, 2026 – Present
Finland
Unity
Senior Data Scientist
August 1, 2021 – April 1, 2026
Unity
Data Scientist
April 1, 2020 – August 1, 2021
Booking.com
Data Scientist - Machine Learning
November 1, 2017 – April 1, 2020
Amsterdam Area, Netherlands
ESB
Data Scientist
July 1, 2016 – October 1, 2017
Ireland
Trinity College Dublin
PhD Student
April 1, 2012 – June 1, 2016
Ireland
Cultural Fit Analysis
The candidate has a strong background in Data Science and Machine Learning across various industries (cybersecurity, gaming, e-commerce, energy). While the target role is 'Backend Engineer', the candidate's experience is heavily skewed towards Data Science/ML Engineering. This represents a significant pivot, and while the underlying technical skills (Python, distributed computing, data pipelines) are relevant, the direct experience in traditional backend engineering (e.g., API development, microservices, system architecture without an ML focus) is not explicitly detailed. This might indicate a potential mismatch for a pure backend engineering role without a strong ML component.
Soft Skills & Operational Fit
The candidate's experience as a Lead Data/AI Scientist and Senior Data Scientist, including leading ML model development tracks, suggests strong leadership, collaboration, and project management skills. The descriptions indicate an ability to work cross-functionally with engineering, security, and product teams. The academic background implies strong research and independent problem-solving capabilities.