I am a data-driven professional transitioning from a background in Mechanical Engineering to Data Analytics. I specialize in transforming complex datasets into actionable business insights using Python, SQL, and Tableau/PowerBI. My experience ranges from engineering predictive models with 97% accuracy to building interactive business intelligence dashboards.
- Goal: Predict customer attrition to improve retention strategies.
- Tech: Python (Pandas, Scikit-Learn, Seaborn), SMOTE for class imbalance.
- Outcome: Developed a classification pipeline optimized for Recall, ensuring high-risk customers are identified before they leave.
- Goal: Visualize regional risk and financial KPIs for insurance claims.
- Tech: Tableau, Excel, Data Storytelling.
- Outcome: Created an interactive dashboard that identifies high-loss geographic "hotspots" to guide stakeholder decision-making.
- BEng (Hons) Dissertation
- Goal: Replace slow CFD simulations with high-speed Neural Networks.
- Tech: Python, Keras, Matplotlib, XFoil.
- Outcome: Achieved 97.58% prediction accuracy, reducing computational time significantly while maintaining precision.
- MSc Dissertation
- Goal: Synchronize and analyze 10M+ features from video/audio streams.
- Tech: TensorFlow, OpenCV, Librosa, MobileNet + BiLSTM.
- Languages: Python (Pandas, NumPy, Scikit-Learn, TensorFlow), SQL, MATLAB.
- Visualization: Tableau, Power BI, Matplotlib, Seaborn.
- Tools: Git/GitHub, Linux (Ubuntu), Excel (Pivot Tables, VLOOKUP).
- Analytical Skills: Predictive Modelling, Statistical Testing, Root Cause Analysis (RCA), EDA.
- LinkedIn: linkedin.com/in/jayspage
- Email: [email protected]
- Location: Preston, UK (Open to Relocation)