Scientific modelling
Years of computational research provide a strong foundation in numerical methods, uncertainty, validation, and physical-system thinking.
Profile
Research depth with delivery discipline.
Derrick combines scientific research depth with practical machine learning delivery. His work connects computational modelling, analytical engineering, and production-focused AI for organisations that need reliable, evidence-led solutions.
Applied machine learning
Work is framed around practical ML delivery: pipelines, model evaluation, cloud deployment, MLOps, and stakeholder-ready outputs.
Clear communication
The page uses concise language, visible proof points, and plain sectioning so recruiters, collaborators, and clients can scan quickly.
Experience
Work across public data, consulting, and research.
This section keeps the career story professional without overloading the page. Each role has a clear organisational context, impact statement, and technical signal.
Professional positioning
Derrick’s public profiles connect data science, machine learning engineering, and a University of Leeds research background. The page presents that combination as a single narrative: rigorous modelling translated into usable AI systems.
Python
PySpark
AWS
FastAPI
MLflow
RAG systems
Scientific computing
2022 — Present
Higher Statistical Data Scientist
Office for National Statistics
Applied machine learning and data-engineering work for analytical platforms, including pipeline modernisation, cloud-based workflows, and internal enablement for analytical teams.
2020 — 2022
Digital Delivery Lead
Accenture UK
Data and digital transformation delivery across cross-functional teams, with emphasis on analytics, customer journey optimisation, and stakeholder management.
2018 — 2020
Founder and Data Science Consultant
Gosso Global Ltd
Independent consulting in machine learning, data strategy, and production-focused analytics for engineering and commercial contexts.
Research years
Computational Fluid Dynamics Researcher
University of Leeds and research collaborators
Research in particle-laden turbulent flows, agglomeration, numerical simulation, and multiphase-flow modelling.
Selected work
Projects that show end-to-end capability.
The project cards have been rewritten to sound credible and specific. They avoid exaggerated marketing language while still showing impact, tools, and delivery context.
Enterprise retrieval system
LLMsReference architecture for document-grounded question answering using retrieval, vector search, orchestration, evaluation, and production delivery practices.
LangChain
GPT models
ChromaDB
Docker
Analytical pipeline modernisation
Data engineeringModernised statistical workflows with scalable processing, cloud storage, reproducible code, and practical training for analysts moving from legacy approaches.
PySpark
AWS S3
Python
R
Marketing response prediction
MLOpsEnd-to-end supervised learning pipeline covering feature engineering, model comparison, experiment tracking, API deployment, and cloud-hosted inference.
CatBoost
FastAPI
MLflow
GitHub Actions
Fraud detection architecture
Risk modelsHybrid anomaly and classification approach for fraud detection, combining model performance with monitoring, interpretability, and operational readiness.
Isolation Forest
XGBoost
LSTM
Monitoring
Research record
Computational work in turbulent multiphase flows.
Derrick’s public research footprint includes computational fluid dynamics, thermofluids engineering, particle-laden flows, and modelling/simulation. The site now presents research as a credibility layer for modern data science rather than a separate academic archive.
76
publications listed on ResearchGate
769
citations listed on ResearchGate at review
23k+
reads listed on ResearchGate at review
Beyond technical work
@donadviser
Through @donadviser, Derrick shares practical reflections on money, mindset, responsibility, and values. The platform sits alongside his technical work as a clear expression of long-term thinking, disciplined learning, and personal growth.
Money
Personal finance, long-term thinking, and practical financial clarity.
Mindset
Consistency, discipline, problem-solving, and learning in public.
Values
Faith-informed reflections on responsibility, leadership, and family life.
Contact
Start a focused conversation.
Reach out for senior data science opportunities, applied AI projects, research collaboration, technical speaking, or consulting conversations.