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Chief Data Scientist at LoopMe
PhD in Machine Learning with 20+ years of experience building and leading teams to apply machine learning in the real world. 27 issued patents. Start-Ups - Key player in taking three start-ups from early stages to successful exit - Understand how to build novel, scaleable software with tight resources, fast - Know how to motivate staff and inspire loyalty - Building company value is why I get up in the morning Management Experience - Considerable experience as Engineering Manager for both development teams and data scientists delivering on-time and on-budget - Managed teams building fully scalable, high availability, real-time, big data applications - Experienced with distributed teams across multiple time zones. - Comfortable interacting at board level Machine Learning Expertise - PhD in Machine Learning - Over twenty years’ experience applying machine learning in the real world, with most of those working in real-time behavioural targeting using big data - Patents: 25 granted, several pending. All machine learning - Live and breathe statistics and probability theory Interests - Blockchain and AI - Distributed Artificial Intelligence - Deep Learning - Optimising on stategic goals using reinforcement learning
University of Bradford
Doctor of Philosophy (PhD), Machine Learning
January 1, 1991 – January 1, 1995
King's College London
Bachelor of Science (BSc), Physics
N/A – Present
LoopMe
Chief Data Scientist
November 1, 2015 – Present
London Area, United Kingdom
NICE Systems
Head of Machine Learning
August 1, 2013 – May 1, 2016
London Area, United Kingdom
Causata
Chief Data Scientist
April 1, 2010 – August 1, 2013
London Area, United Kingdom
Adobe
Chief Data Scientist - Test and Target
January 1, 2009 – January 1, 2010
London Area, United Kingdom
Omniture
Chief Data Scientist - Test and Target
January 1, 2007 – January 1, 2009
London Area, United Kingdom
Touch Clarity
Chief Data Scientist
August 1, 2000 – April 1, 2007
London Area, United Kingdom
Building Research Establishment (BRE)
Research Scientist
January 1, 1996 – January 1, 2000
Watford, England, United Kingdom
Cultural Fit Analysis
The candidate has a strong background in fast-paced, innovative environments, particularly within startups (Touch Clarity, Causata, LoopMe) that were later acquired by larger corporations (Omniture, Adobe, NICE Systems). This demonstrates adaptability to different company cultures and growth stages. Their experience in building and leading teams, coupled with a focus on practical application of machine learning to drive business value, suggests a results-oriented and collaborative approach. The transition from Chief Data Scientist to a Data Analyst role might represent a significant shift in responsibilities, potentially indicating a desire for a more focused, hands-on analytical role, or a mismatch with the target role's typical scope. The breadth of experience across different industries (advertising, customer experience, research) indicates a versatile professional.
Soft Skills & Operational Fit
The candidate's extensive experience in leadership roles (Chief Data Scientist, Head of Machine Learning) across multiple companies, including startups and large enterprises, indicates strong leadership, team management, and strategic thinking skills. Their involvement in patent applications and research collaborations suggests an innovative and problem-solving mindset. The descriptions of building teams, designing architectures, and managing various tasks in startup environments point to adaptability and a hands-on approach. The focus on real-time systems and optimization aligns well with operational demands for high-performance data solutions.