Programming & ML
Python (pandas, sklearn, TensorFlow), SQL, R, GitLab, NumPy, Matplotlib
Hi, I’m Alex Olerimi. Data Scientist.
A curious mind, a love for solving problems, and a belief that great insights start with better questions. I turn complex data into something useful.

01 / THE APPROACH
I’m a data scientist driven by the possibilities hidden in complex information. My work connects technical depth with practical thinking — transforming data into insights that help people make better decisions.
Explore my experiencePython (pandas, sklearn, TensorFlow), SQL, R, GitLab, NumPy, Matplotlib
Classification, model optimisation, SMOTE, feature engineering, CNN/LSTM, hyperparameter tuning
ETL pipelines, Azure (Synapse/Storage), data modelling, large-scale dataset processing
Power BI, DAX, Excel advanced formulas, pivot tables, dashboards
02 / SELECTED WORK
Developed a predictive model to classify tinnitus presence using extracted features from patient data. Built and evaluated multiple ML algorithms (SVM, Random Forest, Logistic Regression), implemented SMOTE, and achieved strong performance.
Applied ML techniques to classify arrhythmia patterns on medical data. Developed automated preprocessing pipeline for signal segmentation and tested models including CNN-based approaches.
Processed and analysed multi-million-row datasets (65M+ Rows) using PySpark and Azure Databricks. Built automated ETL pipeline and delivered insight dashboards for regional crime trends.
03 / THE JOURNEY
• Supported digital document management across departments. • Assisted engineers with data retrieval and technical documentation. • Performed structured data classification, indexing, and archiving. • Ensured data integrity and accessibility for stakeholders.
• Managed daily data processing, documentation, and quality assurance tasks. • Developed structured data collection systems improving reporting accuracy. • Cleaned, validated and updated sensitive records ensuring compliance and accuracy. • Supported management with ad-hoc analysis and produced reports on operational trends.
• Analysed rich operational datasets to support decision-making and customer experience improvements. • Merged, cleaned and processed datasets using SQL, Python, and Excel. • Designed and delivered analytical dashboards using Power BI. • Identified business process inefficiencies and proposed data-driven improvements. • Collaborated cross-functionally with engineering and product teams to translate user and operational needs into actionable insights.
04 / NOTES & PERSPECTIVES
ALWAYS ASKING WHAT’S NEXT