Dean Bellamy
Bristol,United Kingdom
Summary
Data science and machine learning practitioner with a strong academic foundation and early-career industry experience across data science, data engineering and ML workflows. Particularly motivated by hands-on AI engineering, MLOps and cloud-based delivery, and now seeking a structured environment to deepen production engineering skills, learn best practice at scale, and grow as a Machine Learning & AI Engineer.
Overview
6
6
years of professional experience
4
4
years of post-secondary education
1
1
Certification
Work history
Data scientist
Accenture
London
2024.11 - 2025.06
- Worked across Data Science/Engineering and MLOps-adjacent initiatives, supporting infrastructure and pipeline components for analytics and ML systems. This role provided first exposure to cloud-native workflows, deployment tooling, and model orchestration. Helping shape a strong technical foundation for my career transition.
- Apache Spark Data Engineer. Linked data records to analyse entities for financial risk, laundering and evasion. Skills: Linux, Powershell, Hadoop/Spark, Scala, Network Graph Analytics.
- Investigated financial crime and risk detection. Eliminated false positive cases of suspected financial crime, flag suspected fraudulent transactions in real time. Built alternative predictive model solutions to detect potential fraudulent card transactions.
- Transformed ML workflows from data lakes to model-ready pipelines using: Airflow orchestration, MLflow for tracking, GitHub Actions for deployment automation. Skills: AWS ECS, Data Warehousing
Junior Data Scientist
Capgemini
London
2022.03 - 2024.04
- Data Scientist for a market leading restaurant chain, spear-head the research initiative for their market/research team. Produced insights regarding customer-product relationships. Identified pricing gaps and potential financial gain- increased margins by 11% without loss of demand. Built a recommendation model using collaborative and content-based filtering utilising behavioural, transactional and feedback data.
- Methodology: Time Series, Classification, Regression, Rules-Based, Clustering, SciKit-Learn, XGBoost
- Data Engineer for a public sector body. Developed end-to-end data pipelines for schedule reports and data aggregation. Enhanced data-driven decision-making by developing metrics for end users. Tools: AWS; Glue, S3, Redshift
Trade Research Analyst
Office For National Statistics
Cardiff
2019.06 - 2020.04
- Successfully published two papers detailing the UK determinants of trade and the UK FDI Analytical piece. Drafted 2 further papers detailing the economic affairs of the UK automotive industry and exchange rate volatility and the impact it has on UK trade.
- Methodology: Classification & Regression Modeling, Outlier Detection
- Tools/Platforms: Python, SciKit-Learn, NumPy, Pandas, Seaborn, Matplotlib, STATA
Education
MSc - Data Science
Cardiff University
Cardiff 2020.10 - 2022.02
BA Hons - Political Science
University of Kent at Canterbury
Canterbury 2014.09 - 2017.08
Skills
- Python
- Data Science
- Machine Learning
- Deep Learning Frameworks
- PyTorch / Tensorflow
- MLOps
- Data Pipelines / ETL
- Apache Spark/Hadoop
- AWS
- SQL
- Docker
- MLflow / Tracking
- Apache Airflow
- GitHub/Actions
Certification
- AWS Data Engineering, AWS, Mar 2025
- Introduction to Containers w/ Docker, Kubernetes & OpenShift, Coursera, Mar 2025 — Apr 2025
- AWS Modern Solutions Architecture, Hosted by AWS - 2 Weeks - Apr 2025
Languages
English
Native
References
References available upon request
Affiliations
- Outdoors, Fishing, Chess(Blitz), Sim Racing, BBQ's, Travel, New Experiences
Timeline
Data scientist
Accenture
2024.11 - 2025.06
Junior Data Scientist
Capgemini
2022.03 - 2024.04
MSc - Data Science
Cardiff University
2020.10 - 2022.02
Trade Research Analyst
Office For National Statistics
2019.06 - 2020.04
BA Hons - Political Science
University of Kent at Canterbury
2014.09 - 2017.08