uchedavid

Conducted a comprehensive customer churn analysis simulation for XYZ Analytics, identifying critical client retention metrics; proposed data-driven strategies that enhanced retention efforts by 20% and improved overall customer satisfaction rates. Conducted efficient data analysis using Python, including Pandas and NumPy. Employed data visualization techniques for insightful trend interpretation. Completed the engineering and optimization of a random forest model, achieving an 85% accuracy rate in predicting customer churn. Compiled a concise executive summary for the Associate Director, delivering actionable insights for informed decision-making based on the analysis.

Cleaned and prepped data using ydata preprocessor library for easier usability for usage in building of prediction models, saving preprocessing time by up to 60%. Developed and implemented a Random Forest Classifier model leveraging 10,000+ patient data points; achieved an accuracy rate of 95% in predicting patient outcomes, revolutionizing treatment decision-making process. Created a model to predict the level of inflation in countries using Linear Regression algorithm with a 100% accuracy. Collaborated with cross-functional teams to develop comprehensive trend reports utilizing advanced data visualization techniques; these reports provided actionable insights that contributed to a more than 30% increase in operational efficiency across departments.

Diagnostics and maintenance of a Spark Ignition Combustion Engine. Carried out experiments on the behaviour of Airfoils at sonic speed; calculating the drag co-efficient to be 0.2 at a 15 degree angle of attack.

Built machine learning models for supervised and unsupervised learning tasks, and have created visualizations to explain data characteristics and model predictions for non-technical audiences.