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| Experienced client facing Data Scientist/Machine Learning Engineer with | |
| cloud engineering expertise (Azure / Databricks / Synapse / AWS / GCP) and a robust understanding of MLOps | |
| Capable of creating and deploying machine learning models and pipelines | |
| for NLP, recommender systems, deep learning, image recognition, Chatbots | |
| Proficient in leveraging Hugging Face or open.ai platforms for fine-tuning large language models (LLMs) | |
| PROFESSIONAL EXPERIENCE | |
| Data Scientist (contract), Sky TV, London, 02/2024 to present | |
| Development of machine learning algorithms (both supervised and unsupervised) for fraud detection and building of MLOps pipelines | |
| (Google Vertex AI, Kubeflow pipelines, GCP, Big query) | |
| Principal Data Scientist (contract), Neurons Lab, London, 02/2024 to 03/2024 | |
| Responsible for managing the delivery of a Chatbot for the Madrid Mutua Tennis Open (4 Weeks project) | |
| Data Scientist (contract), Deloitte, London, 07/2023 to 11/2023 | |
| On secondment at Fable Data, a leading financial data/payment aggregator and data science company: | |
| Hands on role, responsible for leading a pod/end to end product development for the spanish market. Delivered an algorithm (CI/CD) that classified financial transactions so that the data can be sold as an end product -expected to generate between £500,000 to £1M | |
| (Azure, Python, Data Factory, Synapse, Vscode, Neural Networks, MLflow, NLP, Regex, NER, Git) | |
| Lead Data Scientist (contract), Webhelp , London, 05/2021 to 05/2023 | |
| Developing NLP algorithms using call transcripts in order to analyse and improve CS | |
| Delivering projects from configuring cloud services / running transcriptions to developing models and metrics and mentoring junior staff | |
| Built a monitoring tool (in production) enabling to cut call analysis/coaching time by 80% + NLP apps in Shiny | |
| Analysis of E-Commerce proactive chat initiatives for IKEA UK + insight/dashboard generation ; contributed to a winning team that secured a bid by leveraging incremental sales performance driven by analytical recommendations | |
| Segmentation and automated reporting process for Atos and one of its financial services clients | |
| Stakeholder management and coaching of junior resources, resource planification | |
| (Spark, Python, Databricks/Azure, Power BI) | |
| Data Scientist (contract), EDF Energy, Brighton, 11/2019 to 05/2021 | |
| Part of EDF's BlueLab AI team, aiming to improve customer service through the use of NLP algorithms | |
| Semantic matching of CS electric vehicles Q&A, topic detection from CS conversations, algorithm for address matching, classification, and web traffic analysis | |
| Automated web scraping to cut manual research time by 90% | |
| Stakeholder management and planning of projects | |
| (Python, PyTorch, Spark, NLTK, SpaCy, AWS, Sagemaker, Athena, Tableau, Google Analytics, Agile Environment) | |
| Senior Data Scientist (contract), GVC - Ladbrokes, London, 05/2019 to 11/2019 | |
| Working alongside dev ops and data engineering to deliver a recommender system into production. The recommendation engine was expected to deliver over £1M incremental sales. Also developed visualisation dashboards for monitoring results | |
| (Python, AWS, SageMaker, Athena, Docker, Airflow, PowerBI, Agile Environment) | |
| Senior Data Scientist (contract), Huawei, Milan, 02/2019 to 05/2019 | |
| Social Media Listening and NLP Analytics across key European markets project | |
| (Python, GCP, Selenium, NLP) | |
| Senior Data Scientist (contract), Huawei, Shanghai, 01/2018 to 02/2019 | |
| Development of Machine Learning Algorithms using Python & SQL to improve user experience for flagship handsets: behavioural analysis, app usage prediction, app usage segmentation. Also built an initial ChatBot for Customer Service (using Flow XO) and delivered several NLP projects: CS call classification algorithm to cut processing times dramatically, sentiment analysis, etc | |
| (Python, Keras, NLTK, Gensim, spaCy) | |
| Head of Analytics (consultant), Yocuda (E-Receipts) , London, 03/2014 to 12/2017 | |
| Working on a consultancy basis to deliver analytical projects for ER’s retail clients: | |
| Complete retail segmentation framework using unsupervised learning (Lifestyle, RFM, Mission and Master Segmentation) for a leading UK supermarket used across the business for driving offers, communications and insight | |
| Range reviews, delisting of products, revenue analysis, and campaign evaluation | |
| Improved targeting of campaigns to deliver thousands of incremental spend | |
| (GCP, Python, Bigquery) | |
| Senior Data Scientist (contract), Huawei Ireland, Cork, 07/2013 to 01/2019 | |
| Delivery of Data Mining & Analytics services for Huawei and its major partners across Europe and Asia: | |
| IOT Machine Learning Analytics (supervised + unsupervised) | |
| Object Detection/Recognition and Image Classification | |
| Deep Learning Algorithms (Agtech project for Deutsche Telekom) | |
| Full segmentation project based on mobile app usage for China Unicom (Shanghai) | |
| Churn propensity models for XL Indonesia (Jakarta) using CRM and call quality data | |
| Forecasting algorithms for predicting network events for China Mobile (Hangzhou) | |
| (Scikit Learn, Pandas, PIL, Keras, Tensorflow, Caffe, Dlib, OpenCV, YOLO) | |
| Head of Analytics (UK), Emnos, London, 04/2011 to 07/2013 | |
| Initially joined as an analytics manager. Hands on role, responsible for managing and leading UK analytics department (team of 10): | |
| Planning, recruitment, driving analytical approaches/delivering analytics projects (both | |
| supervised and unsupervised learning) ; part of the UK Management Team | |
| Single customer view and creation of multiple segmentation lenses (value, behavioural, | |
| potential, engagement and attitudinal) across entire Co-op Group | |
| Full segmentation project, propensity model development and data mining (from initial pitch | |
| to delivery and activation/socialisation) for Premier Inn / Whitbread | |
| Other clients included: Camelot, SportingBet, Ladbrokes, BlueSq/Rank & Morrisons | |
| Intelligence Manager, T-Mobile UK, Hatfield, 09/2007 to 03/2011 | |
| Initially joined as a Senior Statistical Analyst. Responsible for the development of churn, cross-sell, up-sell, value and proposition optimization models (logistic regression, CHAID, classification techniques) using SAS and Enterprise Miner 5.2. The models developed saved thousands of customers. This also involved the recruiting and mentoring of analysts/senior analysts | |
| Senior Analyst, Planning-inc, London, 01/2005 to 09/2007 | |
| Working on British Telecom (BT) account to deliver insight, segmentation, propensity models, reporting | |
| Senior Data Analyst, Wunderman Automotive / Y&R, London, 09/2002 to 01/2005 | |
| Production of analytical projects for Wunderman’s key clients (FORD, Jaguar, Mazda and Hewlett Packard) | |
| Product Development Analyst, Schroders Investments, London, 01/2001 to 09/2002 | |
| Used analytics to propose a new pricing structure for funds ; this generated over 8M incremental revenue. The role involved dealing with stakeholders at a very senior level on a regular basis | |
| EDUCATION | |
| LangChain in Action: Develop LLM-Powered Applications 2024 | |
| Azure Data Factory +Synapse Analytics End to End ETL project, Udemy 2023 | |
| Scala & Functional Programming Essentials, Udemy 2023 | |
| MLOps Specialisation: Machine Learning Operations, Duke University, Coursera 2023 | |
| Snowflake the Complete Masterpiece, Udemy 2023 | |
| Looker and LookML, Udemy 2023 | |
| NLP Specialization through deeplearning.ai, Coursera 2022 | |
| Pytorch for Deep Learning with Python, Udemy 2021 | |
| Spark and Python for Big Data with PySpark, Udemy 2020 | |
| Deep Learning Specialization through deeplearning.ai, Coursera 2018 | |
| MBA, Warwick Business School, UK 2006 | |
| B.A. (HONS) International Marketing Management (2:1), Bournemouth University 1995 | |
| French Baccalaureate (distinction), Annecy, France 1991 | |
| TECHNICAL SKILLS | |
| Python, Scala, PyTorch, Spark , KeraS ,AWS Lambda, Langchain, Container Apps, Github Actions, CI/CD, Bigquery , SQL, Athena, Databricks/Azure, Data Factory, Synapse, AWS , S3, GCP, Vertex AI, SageMaker , Docker, PowerBI / DAX, Tableau , Google Data Studio , Looker, Snowflake, Shiny, Roboflow | |
| kubeflow |