
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Strategy & Data Science Leader | Generative AI Transformation | Industry Speaker
• Accomplished data and analytics leader with valuable product development and full project lifecycle experiences for industries ranging from Insurance to Media. • Expertise in providing technical leadership to interdisciplinary stakeholders at varied organisational levels for business outcomes. • Experienced in managing, coaching and growing teams of Machine Learning engineers, data scientists and data engineers. • Ability to look at wider context with expertise in designing data and AI strategies and roadmaps for building products. • Industry expert with established skills in designing and leading the development of scalable intelligent systems and establishing innovative data driven methodologies to extract actionable insight from structured and unstructured data. • Effective public speaking skills displayed by delivering talks in conferences to introduce best Machine Learning practises for industry transformation. • Excellent numerical and analytical skills shown by publishing thirty academic articles and two edited books with more than 3000 citations. • Holder of a patent on an Artificial Intelligence methodology, namely Support Vector Inductive Logic Programming. Core Skills • Strong expertise in Artificial Intelligence, Machine Learning, Data Science, Insurance, Media, Healthcare, Pharmaceuticals, and other application domains. • In-depth knowledge of modern Machine Learning techniques including deep learning approaches, kernel methods, statistical relational learning algorithms, and ensemble methods. • Research and development of algorithms; in particular, classification methods, regression and forecasting algorithms, clustering techniques, parameter estimation methods, feature engineering (feature selection and feature extraction) algorithms, and covariate shift correction and propensity scoring methods. • Adept at computer implement
Royal Holloway, University of London
PhD, Computer Science: Specialisation: Machine Learning
January 1, 1998 – January 1, 2002
Sky
Principal Machine Learning Engineer
August 1, 2022 – Present
Sky
Lead Machine Learning Engineer
February 1, 2021 – July 1, 2022
BP
Data Scientist
June 1, 2019 – December 1, 2020
Direct Line Group
Principal Data Scientist - Artificial Intelligence and Machine Learning
October 1, 2017 – June 1, 2019
Bromley South
LV=
Data Scientist
November 1, 2016 – October 1, 2017
London, Greater London, United Kingdom
Cognizant
Senior Data Scientist, Manager
April 1, 2015 – October 1, 2016
London, United Kingdom
IMS Health
Consultant, Advanced Analytics, RWES, HEOR
January 1, 2014 – April 1, 2015
London, United Kingdom
University of Warwick
Research Fellow
July 1, 2013 – January 1, 2014
University of Leeds
Research Fellow
December 1, 2011 – December 1, 2012
Leeds, United Kingdom
Brunel University
Research Fellow
December 1, 2009 – November 1, 2011
University of Sheffield
Post-doctoral Researcher
April 1, 2006 – October 1, 2006
Sheffield, United Kingdom
Imperial College London
Post-doctoral Researcher
January 1, 2002 – November 1, 2009
London, United Kingdom
Oxford Women’s Leadership Development Programme
Saïd Business School, University of Oxford
June 24, 2026 – Present
Professional Scrum Master (PSM I)
Scrum.org
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic and industry background, with significant experience in research and practical application of Machine Learning. Their diverse project portfolio across various sectors (insurance, healthcare, energy, media) demonstrates adaptability and a broad understanding of data challenges. However, the target role is 'Data Analyst', which is a significant step down from their 'Principal Machine Learning Engineer' and 'Principal Data Scientist' roles. This mismatch in seniority and focus (ML Engineering vs. Data Analysis) could indicate a potential cultural or role fit challenge, despite their strong technical background. The lack of specific projects directly aligned with traditional data analysis (e.g., extensive dashboarding, BI tool expertise, pure reporting) is also noted.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership, mentoring, stakeholder negotiation, and team growth, suggesting strong soft skills and operational fit for senior roles. The Professional Scrum Master certification also indicates an understanding of agile methodologies.