The tools and methods I use, and the areas I am studying.
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Business analysis & delivery
I translate operational needs into requirements, process models and delivery plans.
- Requirements gathering and process/gap analysis
- BRDs and requirements traceability matrices
- Stakeholder coordination, SOPs and KPI design
- Data validation, BPMN/Mermaid and risk tracking
- Agile/Kanban delivery
Data & reporting
My analysis work combines spreadsheets, SQL and Python, supported by DataCamp and analytics training.
- Excel and Google Sheets
- SQL
- Power BI, Tableau and Looker Studio
- Python and Jupyter
- NumPy
- Matplotlib and Seaborn
- Exploratory Data Analysis (EDA)
- Statistics and Probability with statsmodels
- Data cleaning, grain-aware joins and reporting validation
Systems & automation
I connect business workflows and build on my DataCamp training in data engineering and pipeline orchestration.
- ERP/CRM workflows and integration requirements
- Google Apps Script and n8n
- Jira, Git and GitHub
- Microsoft Visio
- Apache Airflow
- ETL & ELT Pipelines
GenAI / LLM-assisted work
Practical assistance across research and delivery.
- Research synthesis and analysis
- Documentation and requirements drafting
- Prototyping, coding and workflow design
- Human review and validation of generated outputs
AI/ML learning
I'm building my AI/ML foundations through DataCamp courses, independent study and local-model experiments.
- Hugging Face
- Python, machine learning and optimisation
- ML/MLOps foundations
- Independent study inspired by MIT OpenCourseWare
- freeCodeCamp Scientific Computing with Python - in progress