Kawkab Abid

With a solid background in software engineering and machine learning, I leverage data science to deliver business insights and improve decision making. I thrive in environment where I bridge the gap between data science and business. Data Scientist familiar with gathering, cleaning and organizing data for use by technical and non-technical personnel. Advanced understanding of statistical, algebraic and other analytical techniques. Highly organized, motivated and diligent with significant background in Mathematics, Statistics, Object Oriented Programming such as Python, Java, SQL and Excel.

Salary Prediction for Future Employee [Python]

• Deployed a salary prediction application for HR and talent acquisition team to help predict future salary for new job positing based on historical hiring data.
• Implemented various ML algorithms in Python OOP for predictive modeling. Gradient Boosting outperformed with Mean Squared Error of 313, increasing the performance by 18%.

Understanding and Predicting Employee Turnover [Python]

• Developed an employee turnover model to understand the attributes for an employee to leave the current company.
• Utilized upsampled and down-sampled method to balance the data and applied 5-fold cross validation using Logistic Regression to determine which method resulted in the best F-1 score. Used SMOTE to train Random Forest and achieved 28.6% improvement in F-1 score over baseline.

Predicting Heart Disease | [Python]

• Developed a ML model using Scikit-Learn which predicts heart diseases of a patient based on various medical attributes.
• Implemented Logistic Regression, K-Nearest Neighbors and Random Forest Classifiers. Achieved 88.5% accuracy score by implementing hyper parameter tuning of Logistic Regression using RandomizedSearchCV and GridSearchCV.

AWS Certified Solutions Architect – Associat