Skills

A blend of data science & ML, cloud & data engineering, and visualisation & communication skills, grounded in practical use cases.

Data Science & ML

Applied

Supervised ML and applied predictive modelling.

Logistic RegressionDecision TreesRandom ForestXGBoostAdaBoostEDA Feature EngineeringHyperparameter TuningModel EvaluationStatistical Modelling Supervised LearningUnsupervised LearningExperiment Design

Programming & Tools

Core

Core stack for analytics and ML workflows.

PythonPandasNumPyscikit-learn MatplotlibSQLJupyterGit R (basic)

Cloud & Data Engineering

Pipelines

Designing and maintaining scalable data pipelines.

AWS S3AWS EMRAWS RedshiftSnowflakeDatabricksMicrosoft Azure ETL / ELTData PipelinesData WranglingData Cleaning

Visualisation & Storytelling

BI

Helping stakeholders understand what the data is saying.

Power BITableauData Narratives Stakeholder Communication

Soft Skills

Ways of working

How I like to work with teams and stakeholders.

Analytical ThinkingStructured Problem-SolvingCollaboration Consulting-style Communication
Want proof? Check Projects and Dashboards.